Study on property and stability mechanism of LAB-AEO-4 system

NASA Astrophysics Data System (ADS)

Song, Kaifei; Ge, Jijiang; Wang, Yang; Zhang, Guicai; Jiang, Ping

2017-04-01

The behaviors of binary blending systems of fatty alcohol polyoxyethylene ether (AEO-4) blended with the laurel amide betaine (LAB) was investigated at 80°C,the results indicated that the optimal ratio of the mixed system of LAB-AEO-4 was 5:2. The stability mechanism of LAB-AEO-4 system was analyzed from three aspects of dynamic surface tension,gas permeation rate and surface rheology.The results showed that the tension of mixed system was easier to achieve balance,the constant of gas permeation rate of the mixed system decreased by about 7% and the elastic modulus and dilational modulus increased by about 2 times compared with the single LAB system.

Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks

PubMed Central

2015-01-01

Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency. PMID:26539722

Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.

PubMed

Jin, Junghwan; Kim, Jinsoo

2015-01-01

Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency.

An Analysis of Fundamental Waffle Mode in Early AEOS Adaptive Optics Images

NASA Astrophysics Data System (ADS)

Makidon, Russell B.; Sivaramakrishnan, Anand; Perrin, Marshall D.; Roberts, Lewis C., Jr.; Oppenheimer, Ben R.; Soummer, Rémi; Graham, James R.

2005-08-01

Adaptive optics (AO) systems have significantly improved astronomical imaging capabilities over the last decade and are revolutionizing the kinds of science possible with 4-5 m class ground-based telescopes. A thorough understanding of AO system performance at the telescope can enable new frontiers of science as observations push AO systems to their performance limits. We look at recent advances with wave-front reconstruction (WFR) on the Advanced Electro-Optical System (AEOS) 3.6 m telescope to show how progress made in improving WFR can be measured directly in improved science images. We describe how a ``waffle mode'' wave-front error (which is not sensed by a Fried geometry Shack-Hartmann wave-front sensor) affects the AO point-spread function. We model details of AEOS AO to simulate a PSF that matches the actual AO PSF in the I band and show that while the older observed AEOS PSF contained several times more waffle error than expected, improved WFR techniques noticeably improve AEOS AO performance. We estimate the impact of these improved WFRs on H-band imaging at AEOS, chosen based on the optimization of the Lyot Project near-infrared coronagraph at this bandpass. Based on observations made at the Maui Space Surveillance System, operated by Detachment 15 of the US Air Force Research Laboratory's Directed Energy Directorate.

Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

NASA Astrophysics Data System (ADS)

E, Jianwei; Bao, Yanling; Ye, Jimin

2017-10-01

As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.

Fuzzy time-series based on Fibonacci sequence for stock price forecasting

NASA Astrophysics Data System (ADS)

Chen, Tai-Liang; Cheng, Ching-Hsue; Jong Teoh, Hia

2007-07-01

Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

Preliminary analysis on hybrid Box-Jenkins - GARCH modeling in forecasting gold price

NASA Astrophysics Data System (ADS)

Yaziz, Siti Roslindar; Azizan, Noor Azlinna; Ahmad, Maizah Hura; Zakaria, Roslinazairimah; Agrawal, Manju; Boland, John

2015-02-01

Gold has been regarded as a valuable precious metal and the most popular commodity as a healthy return investment. Hence, the analysis and prediction of gold price become very significant to investors. This study is a preliminary analysis on gold price and its volatility that focuses on the performance of hybrid Box-Jenkins models together with GARCH in analyzing and forecasting gold price. The Box-Cox formula is used as the data transformation method due to its potential best practice in normalizing data, stabilizing variance and reduces heteroscedasticity using 41-year daily gold price data series starting 2nd January 1973. Our study indicates that the proposed hybrid model ARIMA-GARCH with t-innovation can be a new potential approach in forecasting gold price. This finding proves the strength of GARCH in handling volatility in the gold price as well as overcomes the non-linear limitation in the Box-Jenkins modeling.

Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels

EIA Publications

2003-01-01

This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using Organization for Economic Cooperation and Development (OECD) petroleum inventory levels.

Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm

PubMed Central

2014-01-01

Gold price forecasting has been a hot issue in economics recently. In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue. In this improved algorithm, the conventional roulette selection strategy is discarded. Besides, the convergence statuses in a previous cycle of iteration are fully utilized as feedback messages to manipulate the searching intensity in a subsequent cycle. Experimental results confirm that this new algorithm converges faster than the conventional ABC when tested on some classical benchmark functions and is effective to improve modeling capacity of WNN regarding the gold price forecasting scheme. PMID:24744773

Annual energy outlook 1998 : with projections to 2020

DOT National Transportation Integrated Search

1997-12-01

The analysis in AEO98 focuses primarily on a reference case and four other cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. Forecast tables for these cases are provided in Appendixes...

Waffle mode error in the AEOS adaptive optics point-spread function

NASA Astrophysics Data System (ADS)

Makidon, Russell B.; Sivaramakrishnan, Anand; Roberts, Lewis C., Jr.; Oppenheimer, Ben R.; Graham, James R.

2003-02-01

Adaptive optics (AO) systems have improved astronomical imaging capabilities significantly over the last decade, and have the potential to revolutionize the kinds of science done with 4-5m class ground-based telescopes. However, provided sufficient detailed study and analysis, existing AO systems can be improved beyond their original specified error budgets. Indeed, modeling AO systems has been a major activity in the past decade: sources of noise in the atmosphere and the wavefront sensing WFS) control loop have received a great deal of attention, and many detailed and sophisticated control-theoretic and numerical models predicting AO performance are already in existence. However, in terms of AO system performance improvements, wavefront reconstruction (WFR) and wavefront calibration techniques have commanded relatively little attention. We elucidate the nature of some of these reconstruction problems, and demonstrate their existence in data from the AEOS AO system. We simulate the AO correction of AEOS in the I-band, and show that the magnitude of the `waffle mode' error in the AEOS reconstructor is considerably larger than expected. We suggest ways of reducing the magnitude of this error, and, in doing so, open up ways of understanding how wavefront reconstruction might handle bad actuators and partially-illuminated WFS subapertures.

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

Cigarette Prices and Community Price Comparisons in US Military Retail Stores

PubMed Central

Poston, Walker S.C.; Haddock, Christopher K.; Jahnke, Sara A.; Smith, Elizabeth; Malone, Ruth E.; Jitnarin, Nattinee

2016-01-01

BACKGROUND Tobacco pricing impacts use, yet military retailers sell discounted cigarettes. No systematic research has examined how military retail stores use internal community comparisons to set prices. We analyzed data obtained through a Freedom of Information Act request on community price comparisons used by military retail to set cigarette prices. METHODS Data on cigarette prices were obtained directly from military retailers (exchanges) from January 2013–March 2014. Complete pricing data was provided from exchanges on 114 military installations. RESULTS The average price for a pack of Marlboro cigarettes in military exchanges was $5.51, which was similar to the average lowest community price ($5.45; Mean Difference=−0.06; p=0.104) and almost a $1.00 lower than the average highest price ($6.44). Military retail prices were 2.1%, 6.2%, and 13.7% higher than the lowest, average, and highest community comparisons and 18.2% of exchange prices violated pricing instructions. There was a negative correlation (r = −.21, p = 0.02) between the number of community stores surveyed and exchange cigarette prices. CONCLUSIONS There was no significant difference between prices for cigarettes on military installations and the lowest average community comparison, and in some locations the prices violated DoD policy. US Marine Corps exchanges had the lowest prices, which is of concern given that the Marines also have the highest rates of tobacco use in the DoD. Given the relationship between tobacco product prices and demand, a common minimum (or floor) shelf price for tobacco products should be set for all exchanges and discount coupon redemptions should be prohibited. PMID:27553357

State Renewable Energy Requirements and Goals: Update through 2009 (Update) (released in AEO2010)

EIA Publications

2010-01-01

To the extent possible,Annual Energy Outlook 2010 (AEO) incorporates the impacts of state laws requiring the addition of renewable generation or capacity by utilities doing business in the states. Currently, 30 states and the District of Columbia have enforceable renewable portfolio standards (RPS) or similar laws). Under such standards, each state determines its own levels of generation, eligible technologies, and noncompliance penalties. AEO2010 includes the impacts of all laws in effect as of September 2009 (with the exception of Hawaii, because the National Energy Modeling System provides electricity market projections for the continental United States only).

16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 16 Commercial Practices 1 2012-01-01 2012-01-01 false Retail price comparisons; comparable value... GUIDES AGAINST DECEPTIVE PRICING § 233.2 Retail price comparisons; comparable value comparisons. (a.... Expressed another way, if a number of the principal retail outlets in the area are regularly selling Brand X...

16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 16 Commercial Practices 1 2011-01-01 2011-01-01 false Retail price comparisons; comparable value... GUIDES AGAINST DECEPTIVE PRICING § 233.2 Retail price comparisons; comparable value comparisons. (a.... Expressed another way, if a number of the principal retail outlets in the area are regularly selling Brand X...

16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 16 Commercial Practices 1 2014-01-01 2014-01-01 false Retail price comparisons; comparable value... GUIDES AGAINST DECEPTIVE PRICING § 233.2 Retail price comparisons; comparable value comparisons. (a.... Expressed another way, if a number of the principal retail outlets in the area are regularly selling Brand X...

16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 16 Commercial Practices 1 2013-01-01 2013-01-01 false Retail price comparisons; comparable value... GUIDES AGAINST DECEPTIVE PRICING § 233.2 Retail price comparisons; comparable value comparisons. (a.... Expressed another way, if a number of the principal retail outlets in the area are regularly selling Brand X...

Cigarette prices and community price comparisons in US military retail stores.

PubMed

Poston, Walker S C; Haddock, Christopher K; Jahnke, Sara A; Smith, Elizabeth; Malone, Ruth E; Jitnarin, Nattinee

2016-09-01

Tobacco pricing impacts use, yet military retailers sell discounted cigarettes. No systematic research has examined how military retail stores use internal community comparisons to set prices. We analysed data obtained through a Freedom of Information Act request on community price comparisons used by military retail to set cigarette prices. Data on cigarette prices were obtained directly from military retailers (exchanges) from January 2013 to March 2014. Complete pricing data were obtained from exchanges on 114 military installations. The average price for a pack of Marlboro cigarettes in military exchanges was US$5.51, which was similar to the average lowest community price (US$5.45; mean difference=-0.06; p=0.104) and almost a US$1.00 lower than the average highest price (US$6.44). Military retail prices were 2.1%, 6.2% and 13.7% higher than the lowest, average and highest community comparisons, respectively, and 18.2% of exchange prices violated pricing instructions. There was a negative correlation (r=-0.21, p=0.02) between the number of community stores surveyed and exchange cigarette prices. There was no significant difference between prices for cigarettes on military installations and the lowest average community comparison, and in some locations, the prices violated Department of Defense (DoD) policy. US Marine Corps exchanges had the lowest prices, which is of concern given that the Marines also have the highest rates of tobacco use in the DoD. Given the relationship between tobacco product prices and demand, a common minimum (or floor) shelf price for tobacco products should be set for all exchanges and discount coupon redemptions should be prohibited. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

16 CFR 233.5 - Miscellaneous price comparisons.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Miscellaneous price comparisons. 233.5... DECEPTIVE PRICING § 233.5 Miscellaneous price comparisons. The practices covered in the provisions set forth... principles. For example, retailers should not advertise a retail price as a “wholesale” price. They should...

Factors influencing the difference between forecasted and actual drug sales volumes under the price-volume agreement in South Korea.

PubMed

Park, Sun-Young; Han, Euna; Kim, Jini; Lee, Eui-Kyung

2016-08-01

This study analyzed factors contributing to increases in the actual sales volumes relative to forecasted volumes of drugs under price-volume agreement (PVA) policy in South Korea. Sales volumes of newly listed drugs on the national formulary are monitored under PVA policy. When actual sales volume exceeds the pre-agreed forecasted volume by 30% or more, the drug is subject to price-reduction. Logistic regression assessed the factors related to whether drugs were the PVA price-reduction drugs. A generalized linear model with gamma distribution and log-link assessed the factors influencing the increase in actual volumes compared to forecasted volume in the PVA price-reduction drugs. Of 186 PVA monitored drugs, 34.9% were price-reduction drugs. Drugs marketed by pharmaceutical companies with previous-occupation in the therapeutic markets were more likely to be PVA price-reduction drugs than drugs marketed by firms with no previous-occupation. Drugs of multinational pharmaceutical companies were more likely to be PVA price-reduction drugs than those of domestic companies. Having more alternative existing drugs was significantly associated with higher odds of being PVA price-reduction drugs. Among the PVA price-reduction drugs, the increasing rate of actual volume compared to forecasted volume was significantly higher in drugs with clinical usefulness. By focusing the negotiation efforts on those target drugs, PVA policy can be administered more efficiently with the improved predictability of the drug sales volumes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

16 CFR 233.1 - Former price comparisons.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Former price comparisons. 233.1 Section 233... DECEPTIVE PRICING § 233.1 Former price comparisons. (a) One of the most commonly used forms of bargain advertising is to offer a reduction from the advertiser's own former price for an article. If the former price...

Foreign currency rate forecasting using neural networks

NASA Astrophysics Data System (ADS)

Pandya, Abhijit S.; Kondo, Tadashi; Talati, Amit; Jayadevappa, Suryaprasad

2000-03-01

Neural networks are increasingly being used as a forecasting tool in many forecasting problems. This paper discusses the application of neural networks in predicting daily foreign exchange rates between the USD, GBP as well as DEM. We approach the problem from a time-series analysis framework - where future exchange rates are forecasted solely using past exchange rates. This relies on the belief that the past prices and future prices are very close related, and interdependent. We present the result of training a neural network with historical USD-GBP data. The methodology used in explained, as well as the training process. We discuss the selection of inputs to the network, and present a comparison of using the actual exchange rates and the exchange rate differences as inputs. Price and rate differences are the preferred way of training neural network in financial applications. Results of both approaches are present together for comparison. We show that the network is able to learn the trends in the exchange rate movements correctly, and present the results of the prediction over several periods of time.

Apples with apples: accounting for fuel price risk in comparisons of gas-fired and renewable generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bolinger, Mark; Wiser, Ryan

2003-12-18

For better or worse, natural gas has become the fuel of choice for new power plants being built across the United States. According to the US Energy Information Administration (EIA), natural gas combined-cycle and combustion turbine power plants accounted for 96% of the total generating capacity added in the US between 1999 and 2002--138 GW out of a total of 144 GW. Looking ahead, the EIA expects that gas-fired technology will account for 61% of the 355 GW new generating capacity projected to come on-line in the US up to 2025, increasing the nationwide market share of gas-fired generation frommore » 18% in 2002 to 22% in 2025. While the data are specific to the US, natural gas-fired generation is making similar advances in other countries as well. Regardless of the explanation for (or interpretation of) the empirical findings, however, the basic implications remain the same: one should not blindly rely on gas price forecasts when comparing fixed-price renewable with variable-price gas-fired generation contracts. If there is a cost to hedging, gas price forecasts do not capture and account for it. Alternatively, if the forecasts are at risk of being biased or out of tune with the market, then one certainly would not want to use them as the basis for resource comparisons or investment decisions if a more certain source of data (forwards) existed. Accordingly, assuming that long-term price stability is valued, the most appropriate way to compare the levelized cost of these resources in both cases would be to use forward natural gas price data--i.e. prices that can be locked in to create price certainty--as opposed to uncertain natural gas price forecasts. This article suggests that had utilities and analysts in the US done so over the sample period from November 2000 to November 2003, they would have found gas-fired generation to be at least 0.3-0.6 cents/kWh more expensive (on a levelized cost basis) than otherwise thought. With some renewable resources, in

Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

PubMed

Shabri, Ani; Samsudin, Ruhaidah

2014-01-01

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

PubMed Central

Shabri, Ani; Samsudin, Ruhaidah

2014-01-01

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series. PMID:24895666

Multivariate Time Series Forecasting of Crude Palm Oil Price Using Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Kanchymalay, Kasturi; Salim, N.; Sukprasert, Anupong; Krishnan, Ramesh; Raba'ah Hashim, Ummi

2017-08-01

The aim of this paper was to study the correlation between crude palm oil (CPO) price, selected vegetable oil prices (such as soybean oil, coconut oil, and olive oil, rapeseed oil and sunflower oil), crude oil and the monthly exchange rate. Comparative analysis was then performed on CPO price forecasting results using the machine learning techniques. Monthly CPO prices, selected vegetable oil prices, crude oil prices and monthly exchange rate data from January 1987 to February 2017 were utilized. Preliminary analysis showed a positive and high correlation between the CPO price and soy bean oil price and also between CPO price and crude oil price. Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques. The results were assessed by using criteria of root mean square error (RMSE), means absolute error (MAE), means absolute percentage error (MAPE) and Direction of accuracy (DA). Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method.

International drug price comparisons: quality assessment.

PubMed

Machado, Márcio; O'Brodovich, Ryan; Krahn, Murray; Einarson, Thomas R

2011-01-01

To quantitatively summarize results (i.e., prices and affordability) reported from international drug price comparison studies and assess their methodological quality. A systematic search of the most relevant databases-Medline, Embase, International Pharmaceutical Abstracts (IPA), and Scopus, from their inception to May 2009-was conducted to identify original research comparing international drug prices. International drug price information was extracted and recorded from accepted papers. Affordability was reported as drug prices adjusted for income. Study quality was assessed using six criteria: use of similar countries, use of a representative sample of drugs, selection of specific types of prices, identification of drug packaging, different weights on price indices, and the type of currency conversion used. Of the 1 828 studies identified, 21 were included. Only one study adequately addressed all quality issues. A large variation in study quality was observed due to the many methods used to conduct the drug price comparisons, such as different indices, economic parameters, price types, basket of drugs, and more. Thus, the quality of published studies was considered poor. Results varied across studies, but generally, higher income countries had higher drug prices. However, after adjusting drug prices for affordability, higher income countries had more affordable prices than lower income countries. Differences between drug prices and affordability in different countries were found. Low income countries reported less affordability of drugs, leaving room for potential problems with drug access, and consequently, a negative impact on health. The quality of the literature on this topic needs improvement.

ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

PubMed Central

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561

ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

PubMed

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

Comparison of the economic impact of different wind power forecast systems for producers

NASA Astrophysics Data System (ADS)

Alessandrini, S.; Davò, F.; Sperati, S.; Benini, M.; Delle Monache, L.

2014-05-01

Deterministic forecasts of wind production for the next 72 h at a single wind farm or at the regional level are among the main end-users requirement. However, for an optimal management of wind power production and distribution it is important to provide, together with a deterministic prediction, a probabilistic one. A deterministic forecast consists of a single value for each time in the future for the variable to be predicted, while probabilistic forecasting informs on probabilities for potential future events. This means providing information about uncertainty (i.e. a forecast of the PDF of power) in addition to the commonly provided single-valued power prediction. A significant probabilistic application is related to the trading of energy in day-ahead electricity markets. It has been shown that, when trading future wind energy production, using probabilistic wind power predictions can lead to higher benefits than those obtained by using deterministic forecasts alone. In fact, by using probabilistic forecasting it is possible to solve economic model equations trying to optimize the revenue for the producer depending, for example, on the specific penalties for forecast errors valid in that market. In this work we have applied a probabilistic wind power forecast systems based on the "analog ensemble" method for bidding wind energy during the day-ahead market in the case of a wind farm located in Italy. The actual hourly income for the plant is computed considering the actual selling energy prices and penalties proportional to the unbalancing, defined as the difference between the day-ahead offered energy and the actual production. The economic benefit of using a probabilistic approach for the day-ahead energy bidding are evaluated, resulting in an increase of 23% of the annual income for a wind farm owner in the case of knowing "a priori" the future energy prices. The uncertainty on price forecasting partly reduces the economic benefit gained by using a

Black-Scholes finite difference modeling in forecasting of call warrant prices in Bursa Malaysia

NASA Astrophysics Data System (ADS)

Mansor, Nur Jariah; Jaffar, Maheran Mohd

2014-07-01

Call warrant is a type of structured warrant in Bursa Malaysia. It gives the holder the right to buy the underlying share at a specified price within a limited period of time. The issuer of the structured warrants usually uses European style to exercise the call warrant on the maturity date. Warrant is very similar to an option. Usually, practitioners of the financial field use Black-Scholes model to value the option. The Black-Scholes equation is hard to solve analytically. Therefore the finite difference approach is applied to approximate the value of the call warrant prices. The central in time and central in space scheme is produced to approximate the value of the call warrant prices. It allows the warrant holder to forecast the value of the call warrant prices before the expiry date.

Factors Affecting the Relationship between Crude Oil and Natural Gas Prices (released in AEO2010)

EIA Publications

2010-01-01

Over the 1995-2005 period, crude oil prices and U.S. natural gas prices tended to move together, which supported the conclusion that the markets for the two commodities were connected. Figure 26 illustrates the fairly stable ratio over that period between the price of low-sulfur light crude oil at Cushing, Oklahoma, and the price of natural gas at the Henry Hub on an energy-equivalent basis.

Modeling and forecasting foreign exchange daily closing prices with normal inverse Gaussian

NASA Astrophysics Data System (ADS)

Teneng, Dean

2013-09-01

We fit the normal inverse Gaussian(NIG) distribution to foreign exchange closing prices using the open software package R and select best models by Käärik and Umbleja (2011) proposed strategy. We observe that daily closing prices (12/04/2008 - 07/08/2012) of CHF/JPY, AUD/JPY, GBP/JPY, NZD/USD, QAR/CHF, QAR/EUR, SAR/CHF, SAR/EUR, TND/CHF and TND/EUR are excellent fits while EGP/EUR and EUR/GBP are good fits with a Kolmogorov-Smirnov test p-value of 0.062 and 0.08 respectively. It was impossible to estimate normal inverse Gaussian parameters (by maximum likelihood; computational problem) for JPY/CHF but CHF/JPY was an excellent fit. Thus, while the stochastic properties of an exchange rate can be completely modeled with a probability distribution in one direction, it may be impossible the other way around. We also demonstrate that foreign exchange closing prices can be forecasted with the normal inverse Gaussian (NIG) Lévy process, both in cases where the daily closing prices can and cannot be modeled by NIG distribution.

Forecasting of palm oil price in Malaysia using linear and nonlinear methods

NASA Astrophysics Data System (ADS)

Nor, Abu Hassan Shaari Md; Sarmidi, Tamat; Hosseinidoust, Ehsan

2014-09-01

The first question that comes to the mind is: "How can we predict the palm oil price accurately?" This question is the authorities, policy makers and economist's question for a long period of time. The first reason is that in the recent years Malaysia showed a comparative advantage in palm oil production and has become top producer and exporter in the world. Secondly, palm oil price plays significant role in government budget and represents important source of income for Malaysia, which potentially can influence the magnitude of monetary policies and eventually have an impact on inflation. Thirdly, knowledge on the future trends would be helpful in the planning and decision making procedures and will generate precise fiscal and monetary policy. Daily data on palm oil prices along with the ARIMA models, neural networks and fuzzy logic systems are employed in this paper. Empirical findings indicate that the dynamic neural network of NARX and the hybrid system of ANFIS provide higher accuracy than the ARIMA and static neural network for forecasting the palm oil price in Malaysia.

Price comparisons on the internet based on computational intelligence.

PubMed

Kim, Jun Woo; Ha, Sung Ho

2014-01-01

Information-intensive Web services such as price comparison sites have recently been gaining popularity. However, most users including novice shoppers have difficulty in browsing such sites because of the massive amount of information gathered and the uncertainty surrounding Web environments. Even conventional price comparison sites face various problems, which suggests the necessity of a new approach to address these problems. Therefore, for this study, an intelligent product search system was developed that enables price comparisons for online shoppers in a more effective manner. In particular, the developed system adopts linguistic price ratings based on fuzzy logic to accommodate user-defined price ranges, and personalizes product recommendations based on linguistic product clusters, which help online shoppers find desired items in a convenient manner.

Price Comparisons on the Internet Based on Computational Intelligence

PubMed Central

Kim, Jun Woo; Ha, Sung Ho

2014-01-01

Information-intensive Web services such as price comparison sites have recently been gaining popularity. However, most users including novice shoppers have difficulty in browsing such sites because of the massive amount of information gathered and the uncertainty surrounding Web environments. Even conventional price comparison sites face various problems, which suggests the necessity of a new approach to address these problems. Therefore, for this study, an intelligent product search system was developed that enables price comparisons for online shoppers in a more effective manner. In particular, the developed system adopts linguistic price ratings based on fuzzy logic to accommodate user-defined price ranges, and personalizes product recommendations based on linguistic product clusters, which help online shoppers find desired items in a convenient manner. PMID:25268901

Iao: The New Adaptive Optics Visible Imaging and Photometric System for AEOS

DTIC Science & Technology

2008-09-01

observations of binary stars, asteroids and planets such as Mercury and Mars [2,3,4]. The Visible Imager is also used to take time resolved photometry ...role it takes high spatial resolution imagery of resolved targets. These targets are primarily low Earth orbiting satellites acquired for the...albedo pattern: Comparing the AEOS and TES data sets [5] D.T. Hall et al. 2007, Journal of Spacecraft and Rockets, 44, 910-919, Time - Resolved I-Band

A Toolbox for Teaching Price Comparison to Students with Disabilities

ERIC Educational Resources Information Center

Weng, Pei-Lin; Bouck, Emily C.

2017-01-01

Price comparison is a functional mathematics skill involving purchasing, use of money, and budgeting, with the goal of selecting the best deal based on a person's financial resources (Browder, Spooner, & Trela, 2011). The operational definition of "price comparison" is to compare the magnitudes of the price numbers and then select…

Wind Power Forecasting Error Distributions: An International Comparison; Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, B. M.; Lew, D.; Milligan, M.

2012-09-01

Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique

NASA Astrophysics Data System (ADS)

Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad

2015-11-01

One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.

Arima model and exponential smoothing method: A comparison

NASA Astrophysics Data System (ADS)

Wan Ahmad, Wan Kamarul Ariffin; Ahmad, Sabri

2013-04-01

This study shows the comparison between Autoregressive Moving Average (ARIMA) model and Exponential Smoothing Method in making a prediction. The comparison is focused on the ability of both methods in making the forecasts with the different number of data sources and the different length of forecasting period. For this purpose, the data from The Price of Crude Palm Oil (RM/tonne), Exchange Rates of Ringgit Malaysia (RM) in comparison to Great Britain Pound (GBP) and also The Price of SMR 20 Rubber Type (cents/kg) with three different time series are used in the comparison process. Then, forecasting accuracy of each model is measured by examinethe prediction error that producedby using Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute deviation (MAD). The study shows that the ARIMA model can produce a better prediction for the long-term forecasting with limited data sources, butcannot produce a better prediction for time series with a narrow range of one point to another as in the time series for Exchange Rates. On the contrary, Exponential Smoothing Method can produce a better forecasting for Exchange Rates that has a narrow range of one point to another for its time series, while itcannot produce a better prediction for a longer forecasting period.

High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets

NASA Astrophysics Data System (ADS)

Chen, Tai-Liang; Cheng, Ching-Hsue; Teoh, Hia-Jong

2008-02-01

Stock investors usually make their short-term investment decisions according to recent stock information such as the late market news, technical analysis reports, and price fluctuations. To reflect these short-term factors which impact stock price, this paper proposes a comprehensive fuzzy time-series, which factors linear relationships between recent periods of stock prices and fuzzy logical relationships (nonlinear relationships) mined from time-series into forecasting processes. In empirical analysis, the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) and HSI (Heng Seng Index) are employed as experimental datasets, and four recent fuzzy time-series models, Chen’s (1996), Yu’s (2005), Cheng’s (2006) and Chen’s (2007), are used as comparison models. Besides, to compare with conventional statistic method, the method of least squares is utilized to estimate the auto-regressive models of the testing periods within the databases. From analysis results, the performance comparisons indicate that the multi-period adaptation model, proposed in this paper, can effectively improve the forecasting performance of conventional fuzzy time-series models which only factor fuzzy logical relationships in forecasting processes. From the empirical study, the traditional statistic method and the proposed model both reveal that stock price patterns in the Taiwan stock and Hong Kong stock markets are short-term.

Model documentation, Coal Market Module of the National Energy Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

This report documents the objectives and the conceptual and methodological approach used in the development of the National Energy Modeling System`s (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1998 (AEO98). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s two submodules. These are the Coal Production Submodule (CPS) and the Coal Distribution Submodule (CDS). CMM provides annual forecasts of prices, production, and consumption of coal for NEMS. In general, the CDS integrates the supply inputs from the CPS to satisfy demands for coal from exogenous demand models. The internationalmore » area of the CDS forecasts annual world coal trade flows from major supply to major demand regions and provides annual forecasts of US coal exports for input to NEMS. Specifically, the CDS receives minemouth prices produced by the CPS, demand and other exogenous inputs from other NEMS components, and provides delivered coal prices and quantities to the NEMS economic sectors and regions.« less

Effects of the uncertainty of energy price and water availability forecasts on the operation of Alpine hydropower reservoir systems

NASA Astrophysics Data System (ADS)

Anghileri, D.; Castelletti, A.; Burlando, P.

2016-12-01

European energy markets have experienced dramatic changes in the last years because of the massive introduction of Variable Renewable Sources (VRSs), such as wind and solar power sources, in the generation portfolios in many countries. VRSs i) are intermittent, i.e., their production is highly variable and only partially predictable, ii) are characterized by no correlation between production and demand, iii) have negligible costs of production, and iv) have been largely subsidized. These features result in lower energy prices, but, at the same time, in increased price volatility, and in network stability issues, which pose a threat to traditional power sources because of smaller incomes and higher maintenance costs associated to a more flexible operation of power systems. Storage hydropower systems play an important role in compensating production peaks, both in term of excess and shortage of energy. Traditionally, most of the research effort in hydropower reservoir operation has focused on modeling and forecasting reservoir inflow as well as designing reservoir operation accordingly. Nowadays, price variability may be the largest source of uncertainty in the context of hydropower systems, especially when considering medium-to-large reservoirs, whose storage can easily buffer small inflow fluctuations. In this work, we compare the effects of uncertain inflow and energy price forecasts on hydropower production and profitability. By adding noise to historic inflow and price trajectories, we build a set of synthetic forecasts corresponding to different levels of predictability and assess their impact on reservoir operating policies and performances. The study is conducted on different hydropower systems, including storage systems and pumped-storage systems, with different characteristics, e.g., different inflow-capacity ratios. The analysis focuses on Alpine hydropower systems where the hydrological regime ranges from purely ice and snow-melt dominated to mixed snow

Cancer Drugs: An International Comparison of Postlicensing Price Inflation.

PubMed

Savage, Philip; Mahmoud, Sarah; Patel, Yogin; Kantarjian, Hagop

2017-06-01

The cost of cancer drugs forms a rising proportion of health care budgets worldwide. A number of studies have examined international comparisons of initial cost, but there is little work on postlicensing price increases. To examine this, we compared cancer drug prices at initial sale and subsequent price inflation in the United States and United Kingdom and also reviewed relevant price control mechanisms. The 10 top-selling cancer drugs were selected, and their prices at initial launch and in 2015 were compared. Standard nondiscounted prices were obtained from the relevant annual copies of the RED BOOK and the British National Formulary. At initial marketing, prices were on average 42% higher in the United States than in the United Kingdom. After licensing in the United States, all 10 drugs had price rises averaging an overall annual 8.8% (range, 1.4% to 24.1%) increase. In comparison, in the United Kingdom, six drugs had unchanged prices, two had decreased prices, and two had modest price increases. The overall annual increase in the United Kingdom was 0.24%. Cancer drug prices are rising substantially, both at their initial marketing price and, in the United States, at postlicensing prices. In the United Kingdom, the Pharmaceutical Price Regulation Scheme, an agreement between the government and the pharmaceutical industry, controls health care costs while allowing a return on investment and funds for research. The increasing costs of cancer drugs are approaching the limits of sustainability, and a similar government-industry agreement may allow stability for both health care provision and the pharmaceutical industry in the United States.

Day-ahead crude oil price forecasting using a novel morphological component analysis based model.

PubMed

Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

Price Responsiveness in the AEO2003 NEMS Residential and Commercial Buildings Sector Models

EIA Publications

2003-01-01

This paper describes the demand responses to changes in energy prices in the Annual Energy Outlook 2003 versions of the Residential and Commercial Demand Modules of the National Energy Modeling System (NEMS). It updates a similar paper completed for the Annual Energy Outlook 1999 version of the NEMS.

The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bolinger, Mark A; Wiser, Ryan

2008-09-15

natural gas in the United States over a relatively brief period. Perhaps of most concern is that this dramatic price increase was largely unforeseen. Figure 2 compares the EIA's natural gas wellhead price forecast from each year's Annual Energy Outlook (AEO) going back to 1985 against the average US wellhead price that actually transpired. As shown, our forecasting abilities have proven rather dismal over time, as over-forecasts made in the late 1980's eventually yielded to under-forecasts that have persisted to this day. This historical experience demonstrates that little weight should be placed on any one forecast of future natural gas prices, and that a broad range of future price conditions ought to be considered in planning and investment decisions. Against this backdrop of high, volatile, and unpredictable natural gas prices, increasing the market penetration of renewable generation such as wind, solar, and geothermal power may provide economic benefits to ratepayers by displacing gas-fired generation. These benefits may manifest themselves in several ways. First, the displacement of natural gas-fired generation by increased renewable generation reduces ratepayer exposure to natural gas price risk--i.e., the risk that future gas prices (and by extension future electricity prices) may end up markedly different than expected. Second, this displacement reduces demand for natural gas among gas-fired generators, which, all else equal, will put downward pressure on natural gas prices. Lower natural gas prices in turn benefit both electric ratepayers and other end-users of natural gas. Using analytic approaches that build upon, yet differ from, the past work of others, including Awerbuch (1993, 1994, 2003), Kahn and Stoft (1993), and Humphreys and McClain (1998), this chapter explores each of these two potential 'hedging' benefits of renewable electricity. Though we do not seek to judge whether these two specific benefits outweigh any incremental cost of renewable energy

Modeling spot markets for electricity and pricing electricity derivatives

NASA Astrophysics Data System (ADS)

Ning, Yumei

Spot prices for electricity have been very volatile with dramatic price spikes occurring in restructured market. The task of forecasting electricity prices and managing price risk presents a new challenge for market players. The objectives of this dissertation are: (1) to develop a stochastic model of price behavior and predict price spikes; (2) to examine the effect of weather forecasts on forecasted prices; (3) to price electricity options and value generation capacity. The volatile behavior of prices can be represented by a stochastic regime-switching model. In the model, the means of the high-price and low-price regimes and the probabilities of switching from one regime to the other are specified as functions of daily peak load. The probability of switching to the high-price regime is positively related to load, but is still not high enough at the highest loads to predict price spikes accurately. An application of this model shows how the structure of the Pennsylvania-New Jersey-Maryland market changed when market-based offers were allowed, resulting in higher price spikes. An ARIMA model including temperature, seasonal, and weekly effects is estimated to forecast daily peak load. Forecasts of load under different assumptions about weather patterns are used to predict changes of price behavior given the regime-switching model of prices. Results show that the range of temperature forecasts from a normal summer to an extremely warm summer cause relatively small increases in temperature (+1.5%) and load (+3.0%). In contrast, the increases in prices are large (+20%). The conclusion is that the seasonal outlook forecasts provided by NOAA are potentially valuable for predicting prices in electricity markets. The traditional option models, based on Geometric Brownian Motion are not appropriate for electricity prices. An option model using the regime-switching framework is developed to value a European call option. The model includes volatility risk and allows changes

Stock price prediction using geometric Brownian motion

NASA Astrophysics Data System (ADS)

Farida Agustini, W.; Restu Affianti, Ika; Putri, Endah RM

2018-03-01

Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.

Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

PubMed Central

Zhu, Qing; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614

Comparison of vector autoregressive (VAR) and vector error correction models (VECM) for index of ASEAN stock price

NASA Astrophysics Data System (ADS)

Suharsono, Agus; Aziza, Auliya; Pramesti, Wara

2017-12-01

Capital markets can be an indicator of the development of a country's economy. The presence of capital markets also encourages investors to trade; therefore investors need information and knowledge of which shares are better. One way of making decisions for short-term investments is the need for modeling to forecast stock prices in the period to come. Issue of stock market-stock integration ASEAN is very important. The problem is that ASEAN does not have much time to implement one market in the economy, so it would be very interesting if there is evidence whether the capital market in the ASEAN region, especially the countries of Indonesia, Malaysia, Philippines, Singapore and Thailand deserve to be integrated or still segmented. Furthermore, it should also be known and proven What kind of integration is happening: what A capital market affects only the market Other capital, or a capital market only Influenced by other capital markets, or a Capital market as well as affecting as well Influenced by other capital markets in one ASEAN region. In this study, it will compare forecasting of Indonesian share price (IHSG) with neighboring countries (ASEAN) including developed and developing countries such as Malaysia (KLSE), Singapore (SGE), Thailand (SETI), Philippines (PSE) to find out which stock country the most superior and influential. These countries are the founders of ASEAN and share price index owners who have close relations with Indonesia in terms of trade, especially exports and imports. Stock price modeling in this research is using multivariate time series analysis that is VAR (Vector Autoregressive) and VECM (Vector Error Correction Modeling). VAR and VECM models not only predict more than one variable but also can see the interrelations between variables with each other. If the assumption of white noise is not met in the VAR modeling, then the cause can be assumed that there is an outlier. With this modeling will be able to know the pattern of relationship

Effects of Alaska Oil and Natural Gas Provisions of H. R. 4 and S. 1766 on U.S. Energy Markets

EIA Publications

2002-01-01

On December 20, 2001, Sen. Frank Murkowski, the Ranking Minority Member of the Senate Committee on Energy and Natural Resources requested an analysis of selected portions of Senate Bill 1766 (S. 1766, the Energy Policy Act of 2002) and House Bill H.R. 4 (the Securing America's Future Energy Act of 2001). In response, the Energy Information Administration (EIA) has prepared a series of analyses showing the impacts of each of the selected provisions of the bills on energy supply, demand, and prices, macroeconomic variables where relevant, import dependence, and emissions. The analysis provided is based on the Annual Energy Outlook 2002 (AEO2002) midterm forecasts of energy supply, demand, and prices through 2020.

Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, B. M.; Florita, A.; Orwig, K.

2012-07-01

The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent Systemmore » Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.« less

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.

2013-12-18

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and comparesmore » the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less

Determining the best forecasting method to estimate unitary charges price indexes of PFI data in central region Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Ahmad Kamaruddin, Saadi Bin; Md Ghani, Nor Azura; Mohamed Ramli, Norazan

2013-04-01

The concept of Private Financial Initiative (PFI) has been implemented by many developed countries as an innovative way for the governments to improve future public service delivery and infrastructure procurement. However, the idea is just about to germinate in Malaysia and its success is still vague. The major phase that needs to be given main attention in this agenda is value for money whereby optimum efficiency and effectiveness of each expense is attained. Therefore, at the early stage of this study, estimating unitary charges or materials price indexes in each region in Malaysia was the key objective. This particular study aims to discover the best forecasting method to estimate unitary charges price indexes in construction industry by different regions in the central region of Peninsular Malaysia (Selangor, Federal Territory of Kuala Lumpur, Negeri Sembilan, and Melaka). The unitary charges indexes data used were from year 2002 to 2011 monthly data of different states in the central region Peninsular Malaysia, comprising price indexes of aggregate, sand, steel reinforcement, ready mix concrete, bricks and partition, roof material, floor and wall finishes, ceiling, plumbing materials, sanitary fittings, paint, glass, steel and metal sections, timber and plywood. At the end of the study, it was found that Backpropagation Neural Network with linear transfer function produced the most accurate and reliable results for estimating unitary charges price indexes in every states in central region Peninsular Malaysia based on the Root Mean Squared Errors, where the values for both estimation and evaluation sets were approximately zero and highly significant at p < 0.01. Therefore, artificial neural network is sufficient to forecast construction materials price indexes in Malaysia. The estimated price indexes of construction materials will contribute significantly to the value for money of PFI as well as towards Malaysian economical growth.

Econometrics 101: forecasting demystified

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crow, R.T.

1980-05-01

Forecasting by econometric modeling is described in a commonsense way which omits much of the technical jargon. A trend of continuous growth is no longer an adequate forecasting tool. Today's forecasters must consider rapid changes in price, policies, regulations, capital availability, and the cost of being wrong. A forecasting model is designed by identifying future influences on electricity purchases and quantifying their relationships to each other. A record is produced which can be evaluated and used to make corrections in the models. Residential consumption is used to illustrate how this works and to demonstrate how power consumption is also relatedmore » to the purchase and use of equipment. While models can quantify behavioral relationships, they cannot account for the impacts of non-price factors because of limited data. (DCK)« less

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico.

PubMed

Johansson, Michael A; Reich, Nicholas G; Hota, Aditi; Brownstein, John S; Santillana, Mauricio

2016-09-26

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model.

The impact of wind power on electricity prices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brancucci Martinez-Anido, Carlo; Brinkman, Greg; Hodge, Bri-Mathias

This paper investigates the impact of wind power on electricity prices using a production cost model of the Independent System Operator - New England power system. Different scenarios in terms of wind penetration, wind forecasts, and wind curtailment are modeled in order to analyze the impact of wind power on electricity prices for different wind penetration levels and for different levels of wind power visibility and controllability. The analysis concludes that electricity price volatility increases even as electricity prices decrease with increasing wind penetration levels. The impact of wind power on price volatility is larger in the shorter term (5-minmore » compared to hour-to-hour). The results presented show that over-forecasting wind power increases electricity prices while under-forecasting wind power reduces them. The modeling results also show that controlling wind power by allowing curtailment increases electricity prices, and for higher wind penetrations it also reduces their volatility.« less

Addressing forecast uncertainty impact on CSP annual performance

NASA Astrophysics Data System (ADS)

Ferretti, Fabio; Hogendijk, Christopher; Aga, Vipluv; Ehrsam, Andreas

2017-06-01

This work analyzes the impact of weather forecast uncertainty on the annual performance of a Concentrated Solar Power (CSP) plant. Forecast time series has been produced by a commercial forecast provider using the technique of hindcasting for the full year 2011 in hourly resolution for Ouarzazate, Morocco. Impact of forecast uncertainty has been measured on three case studies, representing typical tariff schemes observed in recent CSP projects plus a spot market price scenario. The analysis has been carried out using an annual performance model and a standard dispatch optimization algorithm based on dynamic programming. The dispatch optimizer has been demonstrated to be a key requisite to maximize the annual revenues depending on the price scenario, harvesting the maximum potential out of the CSP plant. Forecasting uncertainty affects the revenue enhancement outcome of a dispatch optimizer depending on the error level and the price function. Results show that forecasting accuracy of direct solar irradiance (DNI) is important to make best use of an optimized dispatch but also that a higher number of calculation updates can partially compensate this uncertainty. Improvement in revenues can be significant depending on the price profile and the optimal operation strategy. Pathways to achieve better performance are presented by having more updates both by repeatedly generating new optimized trajectories but also more often updating weather forecasts. This study shows the importance of working on DNI weather forecasting for revenue enhancement as well as selecting weather services that can provide multiple updates a day and probabilistic forecast information.

A comparison of GLAS SAT and NMC high resolution NOSAT forecasts from 19 and 11 February 1976

NASA Technical Reports Server (NTRS)

Atlas, R.

1979-01-01

A subjective comparison of the Goddard Laboratory for Atmospheric Sciences (GLAS) and the National Meteorological Center (NMC) high resolution model forecasts is presented. Two cases where NMC's operational model in 1976 had serious difficulties in forecasting for the United States were examined. For each of the cases, the GLAS model forecasts from initial conditions which included satellite sounding data were compared directly to the NMC higher resolution model forecasts, from initial conditions which excluded the satellite data. The comparison showed that the GLAS satellite forecasts significantly improved upon the current NMC operational model's predictions in both cases.

Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets.

PubMed

Pyo, Sujin; Lee, Jaewook; Cha, Mincheol; Jang, Huisu

2017-01-01

The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied to forecast financial markets. This study predicts the trends of the Korea Composite Stock Price Index 200 (KOSPI 200) prices using nonparametric machine learning models: artificial neural network, support vector machines with polynomial and radial basis function kernels. In addition, this study states controversial issues and tests hypotheses about the issues. Accordingly, our results are inconsistent with those of the precedent research, which are generally considered to have high prediction performance. Moreover, Google Trends proved that they are not effective factors in predicting the KOSPI 200 index prices in our frameworks. Furthermore, the ensemble methods did not improve the accuracy of the prediction.

Modeling stock prices in a portfolio using multidimensional geometric brownian motion

NASA Astrophysics Data System (ADS)

Maruddani, Di Asih I.; Trimono

2018-05-01

Modeling and forecasting stock prices of public corporates are important studies in financial analysis, due to their stock price characteristics. Stocks investments give a wide variety of risks. Taking a portfolio of several stocks is one way to minimize risk. Stochastic process of single stock price movements model can be formulated in Geometric Brownian Motion (GBM) model. But for a portfolio that consist more than one corporate stock, we need an expansion of GBM Model. In this paper, we use multidimensional Geometric Brownian Motion model. This paper aims to model and forecast two stock prices in a portfolio. These are PT. Matahari Department Store Tbk and PT. Telekomunikasi Indonesia Tbk on period January 4, 2016 until April 21, 2017. The goodness of stock price forecast value is based on Mean Absolute Percentage Error (MAPE). As the results, we conclude that forecast two stock prices in a portfolio using multidimensional GBM give less MAPE than using GBM for single stock price respectively. We conclude that multidimensional GBM is more appropriate for modeling stock prices, because the price of each stock affects each other.

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico

PubMed Central

Johansson, Michael A.; Reich, Nicholas G.; Hota, Aditi; Brownstein, John S.; Santillana, Mauricio

2016-01-01

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model. PMID:27665707

Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets

PubMed Central

Pyo, Sujin; Lee, Jaewook; Cha, Mincheol

2017-01-01

The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied to forecast financial markets. This study predicts the trends of the Korea Composite Stock Price Index 200 (KOSPI 200) prices using nonparametric machine learning models: artificial neural network, support vector machines with polynomial and radial basis function kernels. In addition, this study states controversial issues and tests hypotheses about the issues. Accordingly, our results are inconsistent with those of the precedent research, which are generally considered to have high prediction performance. Moreover, Google Trends proved that they are not effective factors in predicting the KOSPI 200 index prices in our frameworks. Furthermore, the ensemble methods did not improve the accuracy of the prediction. PMID:29136004

Using time series structural characteristics to analyze grain prices in food insecure countries

USGS Publications Warehouse

Davenport, Frank; Funk, Chris

2015-01-01

Two components of food security monitoring are accurate forecasts of local grain prices and the ability to identify unusual price behavior. We evaluated a method that can both facilitate forecasts of cross-country grain price data and identify dissimilarities in price behavior across multiple markets. This method, characteristic based clustering (CBC), identifies similarities in multiple time series based on structural characteristics in the data. Here, we conducted a simulation experiment to determine if CBC can be used to improve the accuracy of maize price forecasts. We then compared forecast accuracies among clustered and non-clustered price series over a rolling time horizon. We found that the accuracy of forecasts on clusters of time series were equal to or worse than forecasts based on individual time series. However, in the following experiment we found that CBC was still useful for price analysis. We used the clusters to explore the similarity of price behavior among Kenyan maize markets. We found that price behavior in the isolated markets of Mandera and Marsabit has become increasingly dissimilar from markets in other Kenyan cities, and that these dissimilarities could not be explained solely by geographic distance. The structural isolation of Mandera and Marsabit that we find in this paper is supported by field studies on food security and market integration in Kenya. Our results suggest that a market with a unique price series (as measured by structural characteristics that differ from neighboring markets) may lack market integration and food security.

Comparison between stochastic and machine learning methods for hydrological multi-step ahead forecasting: All forecasts are wrong!

NASA Astrophysics Data System (ADS)

Papacharalampous, Georgia; Tyralis, Hristos; Koutsoyiannis, Demetris

2017-04-01

Machine learning (ML) is considered to be a promising approach to hydrological processes forecasting. We conduct a comparison between several stochastic and ML point estimation methods by performing large-scale computational experiments based on simulations. The purpose is to provide generalized results, while the respective comparisons in the literature are usually based on case studies. The stochastic methods used include simple methods, models from the frequently used families of Autoregressive Moving Average (ARMA), Autoregressive Fractionally Integrated Moving Average (ARFIMA) and Exponential Smoothing models. The ML methods used are Random Forests (RF), Support Vector Machines (SVM) and Neural Networks (NN). The comparison refers to the multi-step ahead forecasting properties of the methods. A total of 20 methods are used, among which 9 are the ML methods. 12 simulation experiments are performed, while each of them uses 2 000 simulated time series of 310 observations. The time series are simulated using stochastic processes from the families of ARMA and ARFIMA models. Each time series is split into a fitting (first 300 observations) and a testing set (last 10 observations). The comparative assessment of the methods is based on 18 metrics, that quantify the methods' performance according to several criteria related to the accurate forecasting of the testing set, the capturing of its variation and the correlation between the testing and forecasted values. The most important outcome of this study is that there is not a uniformly better or worse method. However, there are methods that are regularly better or worse than others with respect to specific metrics. It appears that, although a general ranking of the methods is not possible, their classification based on their similar or contrasting performance in the various metrics is possible to some extent. Another important conclusion is that more sophisticated methods do not necessarily provide better forecasts

Novel methodology for pharmaceutical expenditure forecast.

PubMed

Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Mzoughi, Olfa; Toumi, Mondher

2014-01-01

The value appreciation of new drugs across countries today features a disruption that is making the historical data that are used for forecasting pharmaceutical expenditure poorly reliable. Forecasting methods rarely addressed uncertainty. The objective of this project was to propose a methodology to perform pharmaceutical expenditure forecasting that integrates expected policy changes and uncertainty (developed for the European Commission as the 'EU Pharmaceutical expenditure forecast'; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). 1) Identification of all pharmaceuticals going off-patent and new branded medicinal products over a 5-year forecasting period in seven European Union (EU) Member States. 2) Development of a model to estimate direct and indirect impacts (based on health policies and clinical experts) on savings of generics and biosimilars. Inputs were originator sales value, patent expiry date, time to launch after marketing authorization, price discount, penetration rate, time to peak sales, and impact on brand price. 3) Development of a model for new drugs, which estimated sales progression in a competitive environment. Clinical expected benefits as well as commercial potential were assessed for each product by clinical experts. Inputs were development phase, marketing authorization dates, orphan condition, market size, and competitors. 4) Separate analysis of the budget impact of products going off-patent and new drugs according to several perspectives, distribution chains, and outcomes. 5) Addressing uncertainty surrounding estimations via deterministic and probabilistic sensitivity analysis. This methodology has proven to be effective by 1) identifying the main parameters impacting the variations in pharmaceutical expenditure forecasting across countries: generics discounts and penetration, brand price after patent loss, reimbursement rate, the penetration of biosimilars and discount price, distribution chains, and the time

A Comparison Study of Two Numerical Tsunami Forecasting Systems

NASA Astrophysics Data System (ADS)

Greenslade, Diana J. M.; Titov, Vasily V.

2008-12-01

This paper presents a comparison of two tsunami forecasting systems: the NOAA/PMEL system (SIFT) and the Australian Bureau of Meteorology system (T1). Both of these systems are based on a tsunami scenario database and both use the same numerical model. However, there are some major differences in the way in which the scenarios are constructed and in the implementation of the systems. Two tsunami events are considered here: Tonga 2006 and Sumatra 2007. The results show that there are some differences in the distribution of maximum wave amplitude, particularly for the Tonga event, however both systems compare well to the available tsunameter observations. To assess differences in the forecasts for coastal amplitude predictions, the offshore forecast results from both systems were used as boundary conditions for a high-resolution model for Hilo, Hawaii. The minor differences seen between the two systems in deep water become considerably smaller at the tide gauge and both systems compare very well with the observations.

The Second NWRA Flare-Forecasting Comparison Workshop: Methods Compared and Methodology

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, G.; the Flare Forecasting Comparison Group

2013-07-01

The Second NWRA Workshop to compare methods of solar flare forecasting was held 2-4 April 2013 in Boulder, CO. This is a follow-on to the First NWRA Workshop on Flare Forecasting Comparison, also known as the ``All-Clear Forecasting Workshop'', held in 2009 jointly with NASA/SRAG and NOAA/SWPC. For this most recent workshop, many researchers who are active in the field participated, and diverse methods were represented in terms of both the characterization of the Sun and the statistical approaches used to create a forecast. A standard dataset was created for this investigation, using data from the Solar Dynamics Observatory/ Helioseismic and Magnetic Imager (SDO/HMI) vector magnetic field HARP series. For each HARP on each day, 6 hours of data were used, allowing for nominal time-series analysis to be included in the forecasts. We present here a summary of the forecasting methods that participated and the standardized dataset that was used. Funding for the workshop and the data analysis was provided by NASA/Living with a Star contract NNH09CE72C and NASA/Guest Investigator contract NNH12CG10C.

AEO Table Browser

EIA Publications

An interactive data viewer that provides modeled projections of domestic energy markets through 2050, and includes cases with different assumptions of macroeconomic growth, world oil prices, technological progress, and energy policies. With strong domestic production and relatively flat demand, the United States becomes a net energy exporter over the projection period in most cases.

National Hospital Input Price Index

PubMed Central

Freeland, Mark S.; Anderson, Gerard; Schendler, Carol Ellen

1979-01-01

The national community hospital input price index presented here isolates the effects of prices of goods and services required to produce hospital care and measures the average percent change in prices for a fixed market basket of hospital inputs. Using the methodology described in this article, weights for various expenditure categories were estimated and proxy price variables associated with each were selected. The index is calculated for the historical period 1970 through 1978 and forecast for 1979 through 1981. During the historical period, the input price index increased an average of 8.0 percent a year, compared with an average rate of increase of 6.6 percent for overall consumer prices. For the period 1979 through 1981, the average annual increase is forecast at between 8.5 and 9.0 percent. Using the index to deflate growth in expenses, the level of real growth in expenditures per inpatient day (net service intensity growth) averaged 4.5 percent per year with considerable annual variation related to government and hospital industry policies. PMID:10309052

National hospital input price index.

PubMed

Freeland, M S; Anderson, G; Schendler, C E

1979-01-01

The national community hospital input price index presented here isolates the effects of prices of goods and services required to produce hospital care and measures the average percent change in prices for a fixed market basket of hospital inputs. Using the methodology described in this article, weights for various expenditure categories were estimated and proxy price variables associated with each were selected. The index is calculated for the historical period 1970 through 1978 and forecast for 1979 through 1981. During the historical period, the input price index increased an average of 8.0 percent a year, compared with an average rate of increase of 6.6 percent for overall consumer prices. For the period 1979 through 1981, the average annual increase is forecast at between 8.5 and 9.0 per cent. Using the index to deflate growth in expenses, the level of real growth in expenditures per inpatient day (net service intensity growth) averaged 4.5 percent per year with considerable annual variation related to government and hospital industry policies.

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.

2013-07-25

This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load valuesmore » to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less

Novel methodology for pharmaceutical expenditure forecast

PubMed Central

Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Mzoughi, Olfa; Toumi, Mondher

2014-01-01

Background and objective The value appreciation of new drugs across countries today features a disruption that is making the historical data that are used for forecasting pharmaceutical expenditure poorly reliable. Forecasting methods rarely addressed uncertainty. The objective of this project was to propose a methodology to perform pharmaceutical expenditure forecasting that integrates expected policy changes and uncertainty (developed for the European Commission as the ‘EU Pharmaceutical expenditure forecast’; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Methods 1) Identification of all pharmaceuticals going off-patent and new branded medicinal products over a 5-year forecasting period in seven European Union (EU) Member States. 2) Development of a model to estimate direct and indirect impacts (based on health policies and clinical experts) on savings of generics and biosimilars. Inputs were originator sales value, patent expiry date, time to launch after marketing authorization, price discount, penetration rate, time to peak sales, and impact on brand price. 3) Development of a model for new drugs, which estimated sales progression in a competitive environment. Clinical expected benefits as well as commercial potential were assessed for each product by clinical experts. Inputs were development phase, marketing authorization dates, orphan condition, market size, and competitors. 4) Separate analysis of the budget impact of products going off-patent and new drugs according to several perspectives, distribution chains, and outcomes. 5) Addressing uncertainty surrounding estimations via deterministic and probabilistic sensitivity analysis. Results This methodology has proven to be effective by 1) identifying the main parameters impacting the variations in pharmaceutical expenditure forecasting across countries: generics discounts and penetration, brand price after patent loss, reimbursement rate, the penetration of biosimilars and

Essays on oil price volatility and irreversible investment

NASA Astrophysics Data System (ADS)

Pastor, Daniel J.

In chapter 1, we provide an extensive and systematic evaluation of the relative forecasting performance of several models for the volatility of daily spot crude oil prices. Empirical research over the past decades has uncovered significant gains in forecasting performance of Markov Switching GARCH models over GARCH models for the volatility of financial assets and crude oil futures. We find that, for spot oil price returns, non-switching models perform better in the short run, whereas switching models tend to do better at longer horizons. In chapter 2, I investigate the impact of volatility on firms' irreversible investment decisions using real options theory. Cost incurred in oil drilling is considered sunk cost, thus irreversible. I collect detailed data on onshore, development oil well drilling on the North Slope of Alaska from 2003 to 2014. Volatility is modeled by constructing GARCH, EGARCH, and GJR-GARCH forecasts based on monthly real oil prices, and realized volatility from 5-minute intraday returns of oil futures prices. Using a duration model, I show that oil price volatility generally has a negative relationship with the hazard rate of drilling an oil well both when aggregating all the fields, and in individual fields.

Performance Comparison of the European Storm Surge Models and Chaotic Model in Forecasting Extreme Storm Surges

NASA Astrophysics Data System (ADS)

Siek, M. B.; Solomatine, D. P.

2009-04-01

Storm surge modeling has rapidly developed considerably over the past 30 years. A number of significant advances on operational storm surge models have been implemented and tested, consisting of: refining computational grids, calibrating the model, using a better numerical scheme (i.e. more realistic model physics for air-sea interaction), implementing data assimilation and ensemble model forecasts. This paper addresses the performance comparison between the existing European storm surge models and the recently developed methods of nonlinear dynamics and chaos theory in forecasting storm surge dynamics. The chaotic model is built using adaptive local models based on the dynamical neighbours in the reconstructed phase space of observed time series data. The comparison focused on the model accuracy in forecasting a recently extreme storm surge in the North Sea on November 9th, 2007 that hit the coastlines of several European countries. The combination of a high tide, north-westerly winds exceeding 50 mph and low pressure produced an exceptional storm tide. The tidal level was exceeded 3 meters above normal sea levels. Flood warnings were issued for the east coast of Britain and the entire Dutch coast. The Maeslant barrier's two arc-shaped steel doors in the Europe's biggest port of Rotterdam was closed for the first time since its construction in 1997 due to this storm surge. In comparison to the chaotic model performance, the forecast data from several European physically-based storm surge models were provided from: BSH Germany, DMI Denmark, DNMI Norway, KNMI Netherlands and MUMM Belgium. The performance comparison was made over testing datasets for two periods/conditions: non-stormy period (1-Sep-2007 till 14-Oct-2007) and stormy period (15-Oct-2007 till 20-Nov-2007). A scalar chaotic model with optimized parameters was developed by utilizing an hourly training dataset of observations (11-Sep-2005 till 31-Aug-2007). The comparison results indicated the chaotic

Comparison of Observation Impacts in Two Forecast Systems using Adjoint Methods

NASA Technical Reports Server (NTRS)

Gelaro, Ronald; Langland, Rolf; Todling, Ricardo

2009-01-01

An experiment is being conducted to compare directly the impact of all assimilated observations on short-range forecast errors in different operational forecast systems. We use the adjoint-based method developed by Langland and Baker (2004), which allows these impacts to be efficiently calculated. This presentation describes preliminary results for a "baseline" set of observations, including both satellite radiances and conventional observations, used by the Navy/NOGAPS and NASA/GEOS-5 forecast systems for the month of January 2007. In each system, about 65% of the total reduction in 24-h forecast error is provided by satellite observations, although the impact of rawinsonde, aircraft, land, and ship-based observations remains significant. Only a small majority (50- 55%) of all observations assimilated improves the forecast, while the rest degrade it. It is found that most of the total forecast error reduction comes from observations with moderate-size innovations providing small to moderate impacts, not from outliers with very large positive or negative innovations. In a global context, the relative impacts of the major observation types are fairly similar in each system, although regional differences in observation impact can be significant. Of particular interest is the fact that while satellite radiances have a large positive impact overall, they degrade the forecast in certain locations common to both systems, especially over land and ice surfaces. Ongoing comparisons of this type, with results expected from other operational centers, should lead to more robust conclusions about the impacts of the various components of the observing system as well as about the strengths and weaknesses of the methodologies used to assimilate them.

A comparison of generic drug prices in seven European countries: a methodological analysis.

PubMed

Wouters, Olivier J; Kanavos, Panos G

2017-03-31

Policymakers and researchers frequently compare the prices of medicines between countries. Such comparisons often serve as barometers of how pricing and reimbursement policies are performing. The aim of this study was to examine methodological challenges to comparing generic drug prices. We calculated all commonly used price indices based on 2013 IMS Health data on sales of 3156 generic drugs in seven European countries. There were large differences in generic drug prices between countries. However, the results varied depending on the choice of index, base country, unit of volume, method of currency conversion, and therapeutic category. The results also differed depending on whether one looked at the prices charged by manufacturers or those charged by pharmacists. Price indices are a useful statistical approach for comparing drug prices across countries, but researchers and policymakers should interpret price indices with caution given their limitations. Price-index results are highly sensitive to the choice of method and sample. More research is needed to determine the drivers of price differences between countries. The data suggest that some governments should aim to reduce distribution costs for generic drugs.

Toward crustacean without chemicals: a descriptive analysis of consumer response using price comparisons

PubMed Central

Okpala, Charles Odilichukwu R.; Bono, Gioacchino; Pipitone, Vito; Vitale, Sergio; Cannizzaro, Leonardo

2016-01-01

Background To date, there seems to be limited-to-zero emphasis about how consumers perceive crustacean products subject to either chemical and or non-chemical preservative treatments. In addition, studies that investigated price comparisons of crustacean products subject to either chemical or chemical-free preservative methods seem unreported. Objective This study focused on providing some foundational knowledge about how consumers perceive traditionally harvested crustaceans that are either chemical-treated and or free of chemicals, incorporating price comparisons using a descriptive approach. Design The study design employed a questionnaire approach via interview using a computer-assisted telephone system and sampled 1,540 participants across five key locations in Italy. To actualize consumer sensitivity, ‘price’ was the focus given its crucial role as a consumption barrier. Prior to this, variables such as demographic characteristics of participants, frequency of purchasing, quality attributes/factors that limit the consumption of crustaceans were equally considered. Results By price comparisons, consumers are likely to favor chemical-free (modified atmosphere packaging) crustacean products amid a price increase of up to 15%. But, a further price increase such as by 25% could markedly damage consumers’ feelings, which might lead to a considerable number opting out in favor of either chemical-treated or other seafood products. Comparing locations, the studied variables showed no statistical differences (p>0.05). On the contrary, the response weightings fluctuated across the studied categories. Both response weightings and coefficient of variation helped reveal more about how responses deviated per variable categories. Conclusions This study has revealed some foundational knowledge about how consumers perceive traditionally harvested crustaceans that were either chemical-treated or subject to chemical-free preservative up to price sensitivity using Italy as

A COMPARISON OF FLARE FORECASTING METHODS. I. RESULTS FROM THE “ALL-CLEAR” WORKSHOP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnes, G.; Leka, K. D.; Dunn, T.

2016-10-01

Solar flares produce radiation that can have an almost immediate effect on the near-Earth environment, making it crucial to forecast flares in order to mitigate their negative effects. The number of published approaches to flare forecasting using photospheric magnetic field observations has proliferated, with varying claims about how well each works. Because of the different analysis techniques and data sets used, it is essentially impossible to compare the results from the literature. This problem is exacerbated by the low event rates of large solar flares. The challenges of forecasting rare events have long been recognized in the meteorology community, butmore » have yet to be fully acknowledged by the space weather community. During the interagency workshop on “all clear” forecasts held in Boulder, CO in 2009, the performance of a number of existing algorithms was compared on common data sets, specifically line-of-sight magnetic field and continuum intensity images from the Michelson Doppler Imager, with consistent definitions of what constitutes an event. We demonstrate the importance of making such systematic comparisons, and of using standard verification statistics to determine what constitutes a good prediction scheme. When a comparison was made in this fashion, no one method clearly outperformed all others, which may in part be due to the strong correlations among the parameters used by different methods to characterize an active region. For M-class flares and above, the set of methods tends toward a weakly positive skill score (as measured with several distinct metrics), with no participating method proving substantially better than climatological forecasts.« less

An ill-posed problem for the Black-Scholes equation for a profitable forecast of prices of stock options on real market data

NASA Astrophysics Data System (ADS)

Klibanov, Michael V.; Kuzhuget, Andrey V.; Golubnichiy, Kirill V.

2016-01-01

A new empirical mathematical model for the Black-Scholes equation is proposed to forecast option prices. This model includes new interval for the price of the underlying stock, new initial and new boundary conditions. Conventional notions of maturity time and strike prices are not used. The Black-Scholes equation is solved as a parabolic equation with the reversed time, which is an ill-posed problem. Thus, a regularization method is used to solve it. To verify the validity of our model, real market data for 368 randomly selected liquid options are used. A new trading strategy is proposed. Our results indicates that our method is profitable on those options. Furthermore, it is shown that the performance of two simple extrapolation-based techniques is much worse. We conjecture that our method might lead to significant profits of those financial insitutions which trade large amounts of options. We caution, however, that further studies are necessary to verify this conjecture.

Logical design of a decision support system to forecast technology, prices and costs for the national communications system

NASA Astrophysics Data System (ADS)

Williams, K. A.; Partridge, E. C., III

1984-09-01

Originally envisioned as a means to integrate the many systems found throughout the government, the general mission of the NCS continues to be to ensure the survivability of communications during and subsequent to any national emergency. In order to accomplish this mission the NCS is an arrangement of heterogeneous telecommunications systems which are provided by their sponsor Federal agencies. The physical components of Federal telecommunications systems and networks include telephone and digital data switching facilities and primary common user communications centers; Special purpose local delivery message switching and exchange facilities; Government owned or leased radio systems; Technical control facilities which are under exclusive control of a government agency. This thesis describes the logical design of a proposed decision support system for use by the National Communications System in forecasting technology, prices, and costs. It is general in nature and only includes those forecasting models which are suitable for computer implementation. Because it is a logical design it can be coded and applied in many different hardware and/or software configurations.

Annual Energy Outlook 2016 With Projections to 2040

DOE Office of Scientific and Technical Information (OSTI.GOV)

None, None

The Annual Energy Outlook 2016 (AEO2016), prepared by the U.S. Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2040. The projections, focused on U.S. energy markets, are based on results from EIA’s National Energy Modeling System (NEMS). NEMS enables EIA to make projections under alternative, internallyconsistent sets of assumptions. The analysis in AEO2016 focuses on the Reference case and 17 alternative cases. EIA published an Early Release version of the AEO2016 Reference case (including U.S. Environmental Protection Agency’s (EPA) Clean Power Plan (CPP)) and a No CPP case (excluding the CPP) in May 2016.

Forecasting Medicaid Expenditures for Antipsychotic Medications.

PubMed

Slade, Eric P; Simoni-Wastila, Linda

2015-07-01

The ongoing transition from use of mostly branded to mostly generic second-generation antipsychotic medications could bring about a substantial reduction in Medicaid expenditures for antipsychotic medications, a change with critical implications for formulary restrictions on second-generation antipsychotics in Medicaid. This study provided a forecast of the impact of generics on Medicaid expenditures for antipsychotic medications. Quarterly (N=816) state-level aggregate data on outpatient antipsychotic prescriptions in Medicaid between 2008 and 2011 were drawn from the Medicaid state drug utilization database. Annual numbers of prescriptions, expenditures, and cost per prescription were constructed for each antipsychotic medication. Forecasts of antipsychotic expenditures in calendar years 2016 and 2019 were developed on the basis of the estimated percentage reduction in Medicaid expenditures for risperidone, the only second-generation antipsychotic available generically throughout the study period. Two models of savings from generic risperidone use were estimated, one based on constant risperidone prices and the other based on variable risperidone prices. The sensitivity of the expenditure forecast to expected changes in Medicaid enrollment was also examined. In the main model, annual Medicaid expenditures for antipsychotics were forecasted to decrease by $1,794 million (48.8%) by 2016 and by $2,814 million (76.5%) by 2019. Adjustment for variable prices of branded medications and changes in Medicaid enrollment only moderately affected the magnitude of these reductions. Within five years, antipsychotic expenditures in Medicaid may decline to less than half their current levels. Such a spending reduction warrants a reassessment of the continued necessity of formulary restrictions for second-generation antipsychotics in Medicaid.

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

2017-12-01

Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

EIA Publications

2010-01-01

The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

Comparisons of Three-Dimensional Variational Data Assimilation and Model Output Statistics in Improving Atmospheric Chemistry Forecasts

NASA Astrophysics Data System (ADS)

Ma, Chaoqun; Wang, Tijian; Zang, Zengliang; Li, Zhijin

2018-07-01

Atmospheric chemistry models usually perform badly in forecasting wintertime air pollution because of their uncertainties. Generally, such uncertainties can be decreased effectively by techniques such as data assimilation (DA) and model output statistics (MOS). However, the relative importance and combined effects of the two techniques have not been clarified. Here, a one-month air quality forecast with the Weather Research and Forecasting-Chemistry (WRF-Chem) model was carried out in a virtually operational setup focusing on Hebei Province, China. Meanwhile, three-dimensional variational (3DVar) DA and MOS based on one-dimensional Kalman filtering were implemented separately and simultaneously to investigate their performance in improving the model forecast. Comparison with observations shows that the chemistry forecast with MOS outperforms that with 3DVar DA, which could be seen in all the species tested over the whole 72 forecast hours. Combined use of both techniques does not guarantee a better forecast than MOS only, with the improvements and degradations being small and appearing rather randomly. Results indicate that the implementation of MOS is more suitable than 3DVar DA in improving the operational forecasting ability of WRF-Chem.

Study on Comparison of Bidding and Pricing Behavior Distinction between Estimate Methods

NASA Astrophysics Data System (ADS)

Morimoto, Emi; Namerikawa, Susumu

The most characteristic trend on bidding and pricing behavior distinction in recent years is the increasing number of bidders just above the criteria for low-price bidding investigations. The contractor's markup is the difference between the bidding price and the execution price. Therefore, the contractor's markup is the difference between criteria for low-price bidding investigations price and the execution price in the public works bid in Japan. Virtually, bidder's strategies and behavior have been controlled by public engineer's budgets. Estimation and bid are inseparably linked in the Japanese public works procurement system. The trial of the unit price-type estimation method begins in 2004. On another front, accumulated estimation method is one of the general methods in public works. So, there are two types of standard estimation methods in Japan. In this study, we did a statistical analysis on the bid information of civil engineering works for the Ministry of Land, Infrastructure, and Transportation in 2008. It presents several issues that bidding and pricing behavior is related to an estimation method (several estimation methods) for public works bid in Japan. The two types of standard estimation methods produce different results that number of bidders (decide on bid-no bid strategy) and distribution of bid price (decide on mark-up strategy).The comparison on the distribution of bid prices showed that the percentage of the bid concentrated on the criteria for low-price bidding investigations have had a tendency to get higher in the large-sized public works by the unit price-type estimation method, comparing with the accumulated estimation method. On one hand, the number of bidders who bids for public works estimated unit-price tends to increase significantly Public works estimated unit-price is likely to have been one of the factors for the construction companies to decide if they participate in the biddings.

Neural network versus classical time series forecasting models

NASA Astrophysics Data System (ADS)

Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

2017-05-01

Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

Combining forecast weights: Why and how?

NASA Astrophysics Data System (ADS)

Yin, Yip Chee; Kok-Haur, Ng; Hock-Eam, Lim

2012-09-01

This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia.

Valuing hydrological forecasts for a pumped storage assisted hydro facility

NASA Astrophysics Data System (ADS)

Zhao, Guangzhi; Davison, Matt

2009-07-01

SummaryThis paper estimates the value of a perfectly accurate short-term hydrological forecast to the operator of a hydro electricity generating facility which can sell its power at time varying but predictable prices. The expected value of a less accurate forecast will be smaller. We assume a simple random model for water inflows and that the costs of operating the facility, including water charges, will be the same whether or not its operator has inflow forecasts. Thus, the improvement in value from better hydrological prediction results from the increased ability of the forecast using facility to sell its power at high prices. The value of the forecast is therefore the difference between the sales of a facility operated over some time horizon with a perfect forecast, and the sales of a similar facility operated over the same time horizon with similar water inflows which, though governed by the same random model, cannot be forecast. This paper shows that the value of the forecast is an increasing function of the inflow process variance and quantifies how much the value of this perfect forecast increases with the variance of the water inflow process. Because the lifetime of hydroelectric facilities is long, the small increase observed here can lead to an increase in the profitability of hydropower investments.

Energy Intensity Trends in AEO2010 (released in AEO2010)

EIA Publications

2010-01-01

Energy intensity (energy consumption per dollar of real GDP) indicates how much energy a country uses to produce its goods and services. From the early 1950s to the early 1970s, U.S. total primary energy consumption and real GDP increased at nearly the same annual rate. During that period, real oil prices remained virtually flat. In contrast, from the mid-1970s to 2008, the relationship between energy consumption and real GDP growth changed, with primary energy consumption growing at less than one-third the previous average rate and real GDP growth continuing to grow at its historical rate. The decoupling of real GDP growth from energy consumption growth led to a decline in energy intensity that averaged 2.8% per year from 1973 to 2008. In the Annual Energy Outlook 2010 Reference case, energy intensity continues to decline, at an average annual rate of 1.9% from 2008 to 2035.

Short-Term Energy Outlook Model Documentation: Petroleum Product Prices Module

EIA Publications

2015-01-01

The petroleum products price module of the Short-Term Energy Outlook (STEO) model is designed to provide U.S. average wholesale and retail price forecasts for motor gasoline, diesel fuel, heating oil, and jet fuel.

PROJECTIONS OF REGIONAL FUEL OIL AND NATURAL GAS PRICES

EPA Science Inventory

The report presents delivered regional oil and natural gas price forecasts for the industrial and electric utility sectors. Delivered energy price projections by Federal region through the year 2045 are provided for distillate fuel oil, residual fuel oil, and natural gas. Methodo...

Impact of External Price Referencing on Medicine Prices – A Price Comparison Among 14 European Countries

PubMed Central

Leopold, Christine; Mantel-Teeuwisse, Aukje Katja; Seyfang, Leonhard; Vogler, Sabine; de Joncheere, Kees; Laing, Richard Ogilvie; Leufkens, Hubert

2012-01-01

Objectives: This study aims to examine the impact of external price referencing (EPR) on on-patent medicine prices, adjusting for other factors that may affect price levels such as sales volume, exchange rates, gross domestic product (GDP) per capita, total pharmaceutical expenditure (TPE), and size of the pharmaceutical industry. Methods: Price data of 14 on-patent products, in 14 European countries in 2007 and 2008 were obtained from the Pharmaceutical Price Information Service of the Austrian Health Institute. Based on the unit ex-factory prices in EURO, scaled ranks per country and per product were calculated. For the regression analysis the scaled ranks per country and product were weighted; each country had the same sum of weights but within a country the weights were proportional to its sales volume in the year (data obtained from IMS Health). Taking the scaled ranks, several statistical analyses were performed by using the program “R”, including a multiple regression analysis (including variables such as GDP per capita and national industry size). Results: This study showed that on average EPR as a pricing policy leads to lower prices. However, the large variation in price levels among countries using EPR confirmed that the price level is not only driven by EPR. The unadjusted linear regression model confirms that applying EPR in a country is associated with a lower scaled weighted rank (p=0.002). This interaction persisted after inclusion of total pharmaceutical expenditure per capita and GDP per capita in the final model. Conclusions: The study showed that for patented products, prices are in general lower in case the country applied EPR. Nevertheless substantial price differences among countries that apply EPR could be identified. Possible explanations could be found through a correlation between pharmaceutical industry and the scaled price ranks. In conclusion, we found that implementing external reference pricing could lead to lower prices. PMID

Pharmaceutical expenditure forecast model to support health policy decision making.

PubMed

Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

2014-01-01

With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project 'European Union (EU) Pharmaceutical expenditure forecast' - http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). A model was built to assess policy scenarios' impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate, and distribution. Reducing, even slightly, the prices of

Short-Term Energy Outlook Model Documentation: Regional Residential Propane Price Model

EIA Publications

2009-01-01

The regional residential propane price module of the Short-Term Energy Outlook (STEO) model is designed to provide residential retail price forecasts for the 4 Census regions: Northeast, South, Midwest, and West.

Contrail Cirrus Forecasts for the ML-CIRRUS Experiment and Some Comparison Results

NASA Astrophysics Data System (ADS)

Schumann, Ulrich; Graf, Kaspar; Bugliaro, Luca; Dörnbrack, Andreas; Giez, Andreas; Jurkat, Tina; Kaufmann, Stefan; Krämer, Martina; Minikin, Andreas; Schäfler, Andreas; Voigt, Christiane; Wirth, Martin; Zahn, Andreas; Ziereis, Helmut

2015-04-01

rerun with improved ECMWF-NWP data (at one-hour time resolution). The model results are included in the HALO mission data bank, and the results are available for comparison to in-situ data. The data are useful for identifying aircraft and other sources for measured air properties. The joint analysis of observations and model result has basically just started. Preliminary results from comparisons with lidar-measured extinction profiles, in-situ measured humidity, nitrogen oxides, and aerosol and ice particle concentrations, and with meteorological observations (wind, temperature etc.) illustrate the expected gain in insight. The contrail forecasts have been checked by comparison to available data including satellite data and HALO observations. During the campaign, it became obvious that predicted contrail cirrus cover compared qualitatively mostly well with what was found when HALO reached predicted cirrus regions. From the analysis of the measured data, some examples of significant correlation between model results and observations have been found. However, the quantitative agreement is not uniform. As expected, nature is far more variable than a model can predict. The observed optical properties of cirrus and contrails vary far more in time and space than predicted. Local values were often far higher or lower than mean values. A one-to-one correlation between local observations and model results is not to be expected. This inhomogeneity may have consequences for the climate impact of aviation induced cloud changes.

Armed Services Pricing Manual (ASPM). Volume 2: Price Analysis

DTIC Science & Technology

1987-01-01

able to conclude that competition is adequate and thelowest. price is reasonable. You may compare it with the most recent prices paid or the Government ...estimates When price comparisons are not possible, the offered price may be compared with the purcha:ie request estimate (if there is one) or other Government ...both Government and public libraries. There are highly specialized governmental statistical puhlications besides those listed, and there are many

Short-Term Energy Outlook Model Documentation: Regional Residential Heating Oil Price Model

EIA Publications

2009-01-01

The regional residential heating oil price module of the Short-Term Energy Outlook (STEO) model is designed to provide residential retail price forecasts for the 4 census regions: Northeast, South, Midwest, and West.

A comparison of pay-as-bid and marginal pricing in electricity markets

NASA Astrophysics Data System (ADS)

Ren, Yongjun

This thesis investigates the behaviour of electricity markets under marginal and pay-as-bid pricing. Marginal pricing is believed to yield the maximum social welfare and is currently implemented by most electricity markets. However, in view of recent electricity market failures, pay-as-bid has been extensively discussed as a possible alternative to marginal pricing. In this research, marginal and pay-as-bid pricing have been analyzed in electricity markets with both perfect and imperfect competition. The perfect competition case is studied under both exact and uncertain system marginal cost prediction. The comparison of the two pricing methods is conducted through two steps: (i) identify the best offer strategy of the generating companies (gencos); (ii) analyze the market performance under these optimum genco strategies. The analysis results together with numerical simulations show that pay-as-bid and marginal pricing are equivalent in a perfect market with exact system marginal cost prediction. In perfect markets with uncertain demand prediction, the two pricing methods are also equivalent but in an expected value sense. If we compare from the perspective of second order statistics, all market performance measures exhibit much lower values under pay-as-bid than under marginal pricing. The risk of deviating from the mean is therefore much higher under marginal pricing than under pay-as-bid. In an imperfect competition market with exact demand prediction, the research shows that pay-as-bid pricing yields lower consumer payments and lower genco profits. This research provides quantitative evidence that challenges some common claims about pay-as-bid pricing. One is that under pay-as-bid, participants would soon learn how to offer so as to obtain the same or higher profits than what they would have obtained under marginal pricing. This research however shows that, under pay-as-bid, participants can at best earn the same profit or expected profit as under marginal

Comparison of Forecast and Observed Energetics

NASA Technical Reports Server (NTRS)

Baker, W. E.; Brin, Y.

1985-01-01

An energetics analysis scheme was developed to compare the observed kinetic energy balance over North America with that derived from forecast cyclone case. It is found that: (1) the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. The eddy conversion which is stronger in the 12 h forecast than in observations and may be due to several factors is studied; (2) vertical profiles of kinetic energy generation and dissipation exhibit lower and upper tropospheric maxima in both the forecast and observations; and (3) a lag in the observational analysis with the maximum in the observed kinetic energy occurring at 0000 GMT 14 January over the same region as the maximum Eddy conversion 12 h earlier is noted.

Optimal Day-Ahead Scheduling of a Hybrid Electric Grid Using Weather Forecasts

DTIC Science & Technology

2013-12-01

ahead scheduling, Weather forecast , Wind power , Photovoltaic Power 15. NUMBER OF PAGES 107 16. PRICE CODE 17. SECURITY CLASSIFICATION OF...cost can be reached by accurately anticipating the future renewable power productions. This thesis suggests the use of weather forecasts to establish...reached by accurately anticipating the future renewable power productions. This thesis suggests the use of weather forecasts to establish day-ahead

Daily Peak Load Forecasting of Next Day using Weather Distribution and Comparison Value of Each Nearby Date Data

NASA Astrophysics Data System (ADS)

Ito, Shigenobu; Yukita, Kazuto; Goto, Yasuyuki; Ichiyanagi, Katsuhiro; Nakano, Hiroyuki

By the development of industry, in recent years; dependence to electric energy is growing year by year. Therefore, reliable electric power supply is in need. However, to stock a huge amount of electric energy is very difficult. Also, there is a necessity to keep balance between the demand and supply, which changes hour after hour. Consequently, to supply the high quality and highly dependable electric power supply, economically, and with high efficiency, there is a need to forecast the movement of the electric power demand carefully in advance. And using that forecast as the source, supply and demand management plan should be made. Thus load forecasting is said to be an important job among demand investment of electric power companies. So far, forecasting method using Fuzzy logic, Neural Net Work, Regression model has been suggested for the development of forecasting accuracy. Those forecasting accuracy is in a high level. But to invest electric power in higher accuracy more economically, a new forecasting method with higher accuracy is needed. In this paper, to develop the forecasting accuracy of the former methods, the daily peak load forecasting method using the weather distribution of highest and lowest temperatures, and comparison value of each nearby date data is suggested.

Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting

NASA Astrophysics Data System (ADS)

Zhang, Ningning; Lin, Aijing; Shang, Pengjian

2017-07-01

In this paper, we propose a new two-stage methodology that combines the ensemble empirical mode decomposition (EEMD) with multidimensional k-nearest neighbor model (MKNN) in order to forecast the closing price and high price of the stocks simultaneously. The modified algorithm of k-nearest neighbors (KNN) has an increasingly wide application in the prediction of all fields. Empirical mode decomposition (EMD) decomposes a nonlinear and non-stationary signal into a series of intrinsic mode functions (IMFs), however, it cannot reveal characteristic information of the signal with much accuracy as a result of mode mixing. So ensemble empirical mode decomposition (EEMD), an improved method of EMD, is presented to resolve the weaknesses of EMD by adding white noise to the original data. With EEMD, the components with true physical meaning can be extracted from the time series. Utilizing the advantage of EEMD and MKNN, the new proposed ensemble empirical mode decomposition combined with multidimensional k-nearest neighbor model (EEMD-MKNN) has high predictive precision for short-term forecasting. Moreover, we extend this methodology to the case of two-dimensions to forecast the closing price and high price of the four stocks (NAS, S&P500, DJI and STI stock indices) at the same time. The results indicate that the proposed EEMD-MKNN model has a higher forecast precision than EMD-KNN, KNN method and ARIMA.

Short-Term Energy Outlook Model Documentation: Natural Gas Consumption and Prices

EIA Publications

2015-01-01

The natural gas consumption and price modules of the Short-Term Energy Outlook (STEO) model are designed to provide consumption and end-use retail price forecasts for the residential, commercial, and industrial sectors in the nine Census districts and natural gas working inventories in three regions. Natural gas consumption shares and prices in each Census district are used to calculate an average U.S. retail price for each end-use sector.

A price and use comparison of generic versus originator cardiovascular medicines: a hospital study in Chongqing, China

PubMed Central

2013-01-01

Background Developed countries use generic competition to contain pharmaceutical expenditure. China, as a developing and transitional country, has not yet deemed an increase in the use of generic products as important; otherwise, much effort has been made to decrease the drug prices. This paper aims to explore dynamically the price and use comparison of generic and originator drugs in China, and estimate the potential savings of patients from switching originator drugs to generics. Methods A typical hospital in Chongqing, China, was selected to examine the price and use comparisons of 12 cardiovascular drugs from 2006 to 2011. Results The market share of the 12 generic medicines studied in this paper was 34.37% for volume and 31.33% for value in the second half of 2011. The price ratio of generic to originator drugs was between 0.34 and 0.98, and the volume price index of originators to generics was 1.63. The potential savings of patients from switching originator drugs to generics is 65%. Conclusion The market share of the generics was lowering and the weighted mean price kept increasing in face of the strict price control. Under the background of hospitals both prescribing and dispensing medicines, China’s comprehensive healthcare policy makers should take measures from supply and demand sides to promote the consumption of generic medicines. PMID:24093493

Pricing of alcohol in Canada: A comparison of provincial policies and harm-reduction opportunities.

PubMed

Giesbrecht, Norman; Wettlaufer, Ashley; Thomas, Gerald; Stockwell, Tim; Thompson, Kara; April, Nicole; Asbridge, Mark; Cukier, Samantha; Mann, Robert; McAllister, Janet; Murie, Andrew; Pauley, Chris; Plamondon, Laurie; Vallance, Kate

2016-05-01

Alcohol pricing is an effective prevention policy. This paper compares the 10 Canadian provinces on three research-based alcohol pricing policies-minimum pricing, pricing by alcohol content and maintaining prices relative to inflation. The selection of these three policies was based on systematic reviews and seminal research papers. Provincial data for 2012 were obtained from Statistics Canada and relevant provincial ministries, subsequently sent to provincial authorities for verification, and then scored by team members. All provinces, except for Alberta, have minimum prices for at least one beverage type sold in off-premise outlets. All provinces, except for British Columbia and Quebec, have separate (and higher) minimum pricing for on-premise establishments. Regarding pricing on alcohol content, western and central provinces typically scored higher than provinces in Eastern Canada. Generally, minimum prices were lower than the recommended $1.50 per standard drink for off-premise outlets and $3.00 per standard drink in on-premise venues. Seven of 10 provinces scored 60% or higher compared to the ideal on indexing prices to inflation. Prices for a representative basket of alcohol products in Ontario and Quebec have lagged significantly behind inflation since 2006. While examples of evidence-based alcohol pricing policies can be found in every jurisdiction in Canada, significant inter-provincial variation leaves substantial unrealised potential for further reducing alcohol-related harm and costs. This comparative assessment of alcohol price policies provides clear indications of how individual provinces could adjust their pricing policies and practices to improve public health and safety. [Giesbrecht N, Wettlaufer A, Thomas G, Stockwell T, Thompson K, April N, Asbridge M, Cukier S, Mann R, McAllister J, Murie A, Pauley C, Plamondon L, Vallance K. Pricing of alcohol in Canada: A comparison of provincial policies and harm-reduction opportunities. Drug Alcohol Rev

Forecasting fluid milk and cheese demands for the next decade.

PubMed

Schmit, T M; Kaiser, H M

2006-12-01

Predictions of future market demands and farm prices for dairy products are important determinants in developing marketing strategies and farm-production planning decisions. The objective of this report was to use current aggregate forecast data, combined with existing econometric models of demand and supply, to forecast retail demands for fluid milk and cheese and the supply and price of farm milk over the next decade. In doing so, we can investigate whether projections of population and consumer food-spending patterns will extend or alter current consumption trends and examine the implications of future generic advertising strategies for dairy products. To conduct the forecast simulations and appropriately allocate the farm milk supply to various uses, we used a partial equilibrium model of the US domestic dairy sector that segmented the industry into retail, wholesale, and farm markets. Model simulation results indicated that declines in retail per capita demand would persist but at a reduced rate from years past and that retail per capita demand for cheese would continue to grow and strengthen over the next decade. These predictions rely on expected changes in the size of populations of various ages, races, and ethnicities and on existing patterns of spending on food at home and away from home. The combined effect of these forecasted changes in demand levels was reflected in annualized growth in the total farm-milk supply that was similar to growth realized during the past few years. Although we expect nominal farm milk prices to increase over the next decade, we expect real prices (relative to assumed growth in feed costs) to remain relatively stable and show no increase until the end of the forecast period. Supplemental industry model simulations also suggested that net losses in producer revenues would result if only nominal levels of generic advertising spending were maintained in forthcoming years. In fact, if real generic advertising expenditures are

Neural network based load and price forecasting and confidence interval estimation in deregulated power markets

NASA Astrophysics Data System (ADS)

Zhang, Li

With the deregulation of the electric power market in New England, an independent system operator (ISO) has been separated from the New England Power Pool (NEPOOL). The ISO provides a regional spot market, with bids on various electricity-related products and services submitted by utilities and independent power producers. A utility can bid on the spot market and buy or sell electricity via bilateral transactions. Good estimation of market clearing prices (MCP) will help utilities and independent power producers determine bidding and transaction strategies with low risks, and this is crucial for utilities to compete in the deregulated environment. MCP prediction, however, is difficult since bidding strategies used by participants are complicated and MCP is a non-stationary process. The main objective of this research is to provide efficient short-term load and MCP forecasting and corresponding confidence interval estimation methodologies. In this research, the complexity of load and MCP with other factors is investigated, and neural networks are used to model the complex relationship between input and output. With improved learning algorithm and on-line update features for load forecasting, a neural network based load forecaster was developed, and has been in daily industry use since summer 1998 with good performance. MCP is volatile because of the complexity of market behaviors. In practice, neural network based MCP predictors usually have a cascaded structure, as several key input factors need to be estimated first. In this research, the uncertainties involved in a cascaded neural network structure for MCP prediction are analyzed, and prediction distribution under the Bayesian framework is developed. A fast algorithm to evaluate the confidence intervals by using the memoryless Quasi-Newton method is also developed. The traditional back-propagation algorithm for neural network learning needs to be improved since MCP is a non-stationary process. The extended Kalman

Comparison of Forecast and Observed Energetics

NASA Technical Reports Server (NTRS)

Baker, W. E.; Brin, Y.

1984-01-01

An energetics analysis scheme was developed to compare the observed kinetic energy balance over North America with that derived from forecast fields of the GLAS fourth order model for the 13 to 15 January 1979 cyclone case. It is found that: (1) the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. The eddy conversion which is stronger in the 12 h forecast than in observations and may be due to several factors is studied; (2) vertical profiles of kinetic energy generation and dissipation exhibit lower and upper tropospheric maxima in both the forecast and observations; (3) a lag in the observational analysis with the maximum in the observed kinetic energy occurring at 0000 GMT 14 January over the same region as the maximum ddy conversion 12 h earlier is noted.

Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

NASA Technical Reports Server (NTRS)

Watson, Leela R.; Hoeth, Brian; Blottman, Peter F.

2007-01-01

options within each core, provides SMG and NWS MLB with a lot of flexibility. It also creates challenges, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and to determine which configuration will best predict warm season convective initiation in East-Central Florida. Four different combinations of WRF initializations will be run (ADAS-ARW, ADAS-NMM, LAPS-ARW, and LAPS-NMM) at a 4-km resolution over the Florida peninsula and adjacent coastal waters. Five candidate convective initiation days using three different flow regimes over East-Central Florida will be examined, as well as two null cases (non-convection days). Each model run will be integrated 12 hours with three runs per day, at 0900, 1200, and 1500 UTe. ADAS analyses will be generated every 30 minutes using Level II Weather Surveillance Radar-1988 Doppler (WSR-88D) data from all Florida radars to verify the convection forecast. These analyses will be run on the same domain as the four model configurations. To quantify model performance, model output will be subjectively compared to the ADAS analyses of convection to determine forecast accuracy. In addition, a subjective comparison of the performance of the ARW using a high-resolution local grid with 2-way nesting, I-way nesting, and no nesting will be made for select convective initiation cases. The inner grid will cover the East-Central Florida region at a resolution of 1.33 km. The authors will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for predicting warm season convective initiation over East-Central Florida.

The fractal feature and price trend in the gold future market at the Shanghai Futures Exchange (SFE)

NASA Astrophysics Data System (ADS)

Wu, Binghui; Duan, Tingting

2017-05-01

The price of gold future is affected by many factors, which include the fluctuation of gold price and the change of trading environment. Fractal analysis can help investors gain better understandings of the price fluctuation and make reasonable investment decisions in the gold future market. After analyzing gold future price from January 2th, 2014 to April 12th, 2016 at the Shanghai Futures Exchange (SFE) in China, the conclusion is drawn that the gold future market has sustainability in each trading day, with all Hurst indexes greater than 0.5. The changing features of Hurst index indicate the sustainability of gold future market is strengthened first and weakened then. As a complicatedly nonlinear system, the gold future market can be well reflected by Elman neural network, which is capable of memorizing previous prices and particularly suited for forecasting time series in comparison with other types of neural networks. After analyzing the price trend in the gold future market, the results show that the relative error between the actual value of gold future and the predictive value of Elman neural network is smaller. This model that has a better performance in data fitting and predication, can help investors analyze and foresee the price tendency in the gold future market.

Analyzing the Stability of Price Response Functions: Measuring the Influence of Different Parameters in a Monte Carlo Comparison

NASA Astrophysics Data System (ADS)

Brusch, Michael; Baier, Daniel

The usage and the estimation of price response function is very important for strategic marketing decisions. Typically price response functions with an empirical basis are used. However, such price response functions are subject to a lot of disturbing influence factors, e.g., the assumed profit maximum price and the assumed corresponding quantity of sales. In such cases, the question how stable the found price response function is was not answered sufficiently up to now. In this paper, the question will be pursued how much (and what kind of) errors in market research are pardonable for a stable price response function. For the comparisons, a factorial design with synthetically generated and disturbed data is used.

Comparing a number line and audio prompts in supporting price comparison by students with intellectual disability.

PubMed

Bouck, Emily C; Satsangi, Rajiv; Bartlett, Whitney

2016-01-01

Price comparison is an important and complex skill, but it lacks sufficient research attention in terms of educating secondary students with intellectual disability and/or autism spectrum disorder. This alternating treatment design study compared the use of a paper-based number line and audio prompts delivered via an audio recorder to support three secondary students with intellectual disability to independently and accuracy compare the price of three separate grocery items. The study consisted of 22 sessions, spread across baseline, intervention, best treatment, and two different generalization phases. Data were collected on the percent of task analysis steps completed independently, the type of prompts needed, students' accuracy selecting the lowest priced item, and task completion time. With both intervention conditions, students were able to independently complete the task analysis steps as well as accurately select the lowest priced item and decrease their task completion time. For two of the students, the audio recorder condition resulted in the greatest independence and for one the number line. For only one student was the condition with the greatest independence also the condition for the highest rate of accuracy. The results suggest both tools can support students with price comparison. Yet, audio recorders offer students and teachers an age-appropriate and setting-appropriate option. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Technical Analysis Information Fusion Approach for Stock Price Analysis and Modeling

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

In this paper, we address the problem of technical analysis information fusion in improving stock market index-level prediction. We present an approach for analyzing stock market price behavior based on different categories of technical analysis metrics and a multiple predictive system. Each category of technical analysis measures is used to characterize stock market price movements. The presented predictive system is based on an ensemble of neural networks (NN) coupled with particle swarm intelligence for parameter optimization where each single neural network is trained with a specific category of technical analysis measures. The experimental evaluation on three international stock market indices and three individual stocks show that the presented ensemble-based technical indicators fusion system significantly improves forecasting accuracy in comparison with single NN. Also, it outperforms the classical neural network trained with index-level lagged values and NN trained with stationary wavelet transform details and approximation coefficients. As a result, technical information fusion in NN ensemble architecture helps improving prediction accuracy.

Annual Energy Outlook Retrospective Review

EIA Publications

2015-01-01

The Annual Energy Outlook Retrospective Review provides a yearly comparison between realized energy outcomes and the Reference case projections included in previous Annual Energy Outlooks (AEO) beginning with 1982. This edition of the report adds the AEO 2012 projections and updates the historical data to incorporate the latest data revisions.

Economic indicators selection for crime rates forecasting using cooperative feature selection

NASA Astrophysics Data System (ADS)

Alwee, Razana; Shamsuddin, Siti Mariyam Hj; Salleh Sallehuddin, Roselina

2013-04-01

Features selection in multivariate forecasting model is very important to ensure that the model is accurate. The purpose of this study is to apply the Cooperative Feature Selection method for features selection. The features are economic indicators that will be used in crime rate forecasting model. The Cooperative Feature Selection combines grey relational analysis and artificial neural network to establish a cooperative model that can rank and select the significant economic indicators. Grey relational analysis is used to select the best data series to represent each economic indicator and is also used to rank the economic indicators according to its importance to the crime rate. After that, the artificial neural network is used to select the significant economic indicators for forecasting the crime rates. In this study, we used economic indicators of unemployment rate, consumer price index, gross domestic product and consumer sentiment index, as well as data rates of property crime and violent crime for the United States. Levenberg-Marquardt neural network is used in this study. From our experiments, we found that consumer price index is an important economic indicator that has a significant influence on the violent crime rate. While for property crime rate, the gross domestic product, unemployment rate and consumer price index are the influential economic indicators. The Cooperative Feature Selection is also found to produce smaller errors as compared to Multiple Linear Regression in forecasting property and violent crime rates.

Short-term data forecasting based on wavelet transformation and chaos theory

NASA Astrophysics Data System (ADS)

Wang, Yi; Li, Cunbin; Zhang, Liang

2017-09-01

A sketch of wavelet transformation and its application was given. Concerning the characteristics of time sequence, Haar wavelet was used to do data reduction. After processing, the effect of “data nail” on forecasting was reduced. Chaos theory was also introduced, a new chaos time series forecasting flow based on wavelet transformation was proposed. The largest Lyapunov exponent was larger than zero from small data sets, it verified the data change behavior still met chaotic behavior. Based on this, chaos time series to forecast short-term change behavior could be used. At last, the example analysis of the price from a real electricity market showed that the forecasting method increased the precision of the forecasting more effectively and steadily.

Pharmaceutical expenditure forecast model to support health policy decision making

PubMed Central

Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

2014-01-01

Background and objective With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project ‘European Union (EU) Pharmaceutical expenditure forecast’ – http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Methods A model was built to assess policy scenarios’ impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Results Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Conclusions Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate

The Frozen Price Game

ERIC Educational Resources Information Center

Alden, Lori

2003-01-01

In this article, the author discusses the educational frozen price game she developed to teach the basic economic principle of price allocation. In addition to demonstrating the advantages of price allocation, the game also illustrates such concepts as opportunity costs, cost benefit comparisons, and the trade-off between efficiency and equity.…

Comparison of tiered formularies and reference pricing policies: a systematic review

PubMed Central

Morgan, Steve; Hanley, Gillian; Greyson, Devon

2009-01-01

Objectives To synthesize methodologically comparable evidence from the published literature regarding the outcomes of tiered formularies and therapeutic reference pricing of prescription drugs. Methods We searched the following electronic databases: ABI/Inform, CINAHL, Clinical Evidence, Digital Dissertations & Theses, Evidence-Based Medicine Reviews (which incorporates ACP Journal Club, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Cochrane Methodology Register, Database of Abstracts of Reviews of Effectiveness, Health Technology Assessments and NHS Economic Evaluation Database), EconLit, EMBASE, International Pharmaceutical Abstracts, MEDLINE, PAIS International and PAIS Archive, and the Web of Science. We also searched the reference lists of relevant articles and several grey literature sources. We sought English-language studies published from 1986 to 2007 that examined the effects of either therapeutic reference pricing or tiered formularies, reported on outcomes relevant to patient care and cost-effectiveness, and employed quantitative study designs that included concurrent or historical comparison groups. We abstracted and assessed potentially appropriate articles using a modified version of the data abstraction form developed by the Cochrane Effective Practice and Organisation of Care Group. Results From an initial list of 2964 citations, 12 citations (representing 11 studies) were deemed eligible for inclusion in our review: 3 studies (reported in 4 articles) of reference pricing and 8 studies of tiered formularies. The introduction of reference pricing was associated with reduced plan spending, switching to preferred medicines, reduced overall drug utilization and short-term increases in the use of physician services. Reference pricing was not associated with adverse health impacts. The introduction of tiered formularies was associated with reduced plan expenditures, greater patient costs and increased rates of

A Comparison of the Forecast Skills among Three Numerical Models

NASA Astrophysics Data System (ADS)

Lu, D.; Reddy, S. R.; White, L. J.

2003-12-01

Three numerical weather forecast models, MM5, COAMPS and WRF, operating with a joint effort of NOAA HU-NCAS and Jackson State University (JSU) during summer 2003 have been chosen to study their forecast skills against observations. The models forecast over the same region with the same initialization, boundary condition, forecast length and spatial resolution. AVN global dataset have been ingested as initial conditions. Grib resolution of 27 km is chosen to represent the current mesoscale model. The forecasts with the length of 36h are performed to output the result with 12h interval. The key parameters used to evaluate the forecast skill include 12h accumulated precipitation, sea level pressure, wind, surface temperature and dew point. Precipitation is evaluated statistically using conventional skill scores, Threat Score (TS) and Bias Score (BS), for different threshold values based on 12h rainfall observations whereas other statistical methods such as Mean Error (ME), Mean Absolute Error(MAE) and Root Mean Square Error (RMSE) are applied to other forecast parameters.

Flood Forecasting in Wales: Challenges and Solutions

NASA Astrophysics Data System (ADS)

How, Andrew; Williams, Christopher

2015-04-01

With steep, fast-responding river catchments, exposed coastal reaches with large tidal ranges and large population densities in some of the most at-risk areas; flood forecasting in Wales presents many varied challenges. Utilising advances in computing power and learning from best practice within the United Kingdom and abroad have seen significant improvements in recent years - however, many challenges still remain. Developments in computing and increased processing power comes with a significant price tag; greater numbers of data sources and ensemble feeds brings a better understanding of uncertainty but the wealth of data needs careful management to ensure a clear message of risk is disseminated; new modelling techniques utilise better and faster computation, but lack the history of record and experience gained from the continued use of more established forecasting models. As a flood forecasting team we work to develop coastal and fluvial forecasting models, set them up for operational use and manage the duty role that runs the models in real time. An overview of our current operational flood forecasting system will be presented, along with a discussion on some of the solutions we have in place to address the challenges we face. These include: • real-time updating of fluvial models • rainfall forecasting verification • ensemble forecast data • longer range forecast data • contingency models • offshore to nearshore wave transformation • calculation of wave overtopping

Essays in financial transmission rights pricing

NASA Astrophysics Data System (ADS)

Posner, Barry

This work examines issues in the pricing of financial transmission rights in the PJM market region. The US federal government is advocating the creation of large-scale, not-for-profit regional transmission organizations to increase the efficiency of the transmission of electricity. As a non-profit entity, PJM needs to allocate excess revenues collected as congestion rents, and the participants in the transmission markets need to be able to hedge their exposure to congestion rents. For these purposes, PJM has developed an instrument known as the financial transmission right (FTR). This research, utilizing a new data set assembled by the author, looks at two aspects of the FTR market. The first chapter examines the problem of forecasting congestion in a transmission grid. In the PJM FTR system firms bid in a competitive auction for FTRs that cover a period of one month. The auctions take place in the middle of the previous month; therefore firms have to forecast congestion rents for the period two to six weeks after the auction. The common methods of forecasting congestion are either time-series models or full-information engineering studies. In this research, the author develops a forecasting system that is more economically grounded than a simple time-series model, but requires less information than an engineering model. This method is based upon the arbitrage-cost methodology, whereby congesting is calculated as the difference of two non-observable variables: the transmission price difference that would exist in the total absence of transmission capacity between two nodes, and the ability of the existing transmission to reduced that price difference. If the ability to reduce the price difference is greater than the price difference, then the cost of electricity at each node will be the same, and congestion rent will be zero. If transmission capacity limits are binding on the flow of power, then a price difference persists and congestion rents exist. Three

Application of empirical mode decomposition with local linear quantile regression in financial time series forecasting.

PubMed

Jaber, Abobaker M; Ismail, Mohd Tahir; Altaher, Alsaidi M

2014-01-01

This paper mainly forecasts the daily closing price of stock markets. We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). We use the proposed technique, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.

Reforming antiretroviral price negotiations and public procurement: the Mexican experience.

PubMed

Adesina, Adebiyi; Wirtz, Veronika J; Dratler, Sandra

2013-01-01

Since antiretroviral (ARV) medicines represent one of the most costly components of therapy for HIV in middle-income countries, ensuring their efficient procurement is highly relevant. In 2008, Mexico created a national commission for the negotiation of ARV prices to achieve price reductions for their public HIV treatment programmes. The objective of this study is to assess the immediate impact of the creation of the Mexican Commission for Price Negotiation on ARV prices and expenditures. A longitudinal retrospective analysis of procurement prices, volumes and type of the most commonly prescribed ARVs procured by the two largest providers of HIV/AIDS care in Mexico between 2004 and 2009 was carried out. These analyses were combined with 26 semi-structured key informant interviews to identify changes in the procurement process. Prices for ARVs dropped by an average of 38% after the first round of negotiations, indicating that the Commission was successful in price negotiations. However, when compared with other upper-middle-income countries, Mexico continues to pay an average of six times more for ARVs. The Commission's negotiations were successful in achieving lower ARV prices. However, price reduction in upper-middle-income countries suggests that the price decrease in Mexico cannot be entirely attributed to the Commission's first round of negotiations. In addition, key informants identified inefficiencies in the forecasting and procurement processes possibly affecting the efficiency of the negotiation process. A comprehensive approach to improving efficiency in the purchasing and delivery of ARVs is necessary, including a better clarification in the roles and responsibilities of the Commission, improving supply data collection and integration in forecasting and procurement, and the creation of a support system to monitor and provide feedback on patient ARV use.

Air Pollution Forecasts: An Overview

PubMed Central

Bai, Lu; Wang, Jianzhou; Lu, Haiyan

2018-01-01

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

Air Pollution Forecasts: An Overview.

PubMed

Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

2018-04-17

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

76 FR 18425 - Energy Conservation Program: Data Collection and Comparison With Forecasted Unit Sales of Five...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-04

... Program: Data Collection and Comparison With Forecasted Unit Sales of Five Lamp Types AGENCY: Office of...) Collect unit sales data for each of the five lamp types for calendar years 1990 through 2006 in order to... continue to track rough service lamp sales data and will not initiate regulatory action for this lamp type...

Does the OVX matter for volatility forecasting? Evidence from the crude oil market

NASA Astrophysics Data System (ADS)

Lv, Wendai

2018-02-01

In this paper, I investigate that whether the OVX and its truncated parts with a certain threshold can significantly help in forecasting the oil futures price volatility basing on the Heterogeneous Autoregressive model of Realized Volatility (HAR-RV). In-sample estimation results show that the OVX has a significantly positive impact on futures volatility. The impact of large OVX on future volatility has slightly powerful compared to the small ones. Moreover, the HARQ-RV model outperforms the HAR-RV in predicting the oil futures volatility. More importantly, the decomposed OVX have more powerful in forecasting the oil futures price volatility compared to the OVX itself.

The Forecast Interpretation Tool—a Monte Carlo technique for blending climatic distributions with probabilistic forecasts

USGS Publications Warehouse

Husak, Gregory J.; Michaelsen, Joel; Kyriakidis, P.; Verdin, James P.; Funk, Chris; Galu, Gideon

2011-01-01

Probabilistic forecasts are produced from a variety of outlets to help predict rainfall, and other meteorological events, for periods of 1 month or more. Such forecasts are expressed as probabilities of a rainfall event, e.g. being in the upper, middle, or lower third of the relevant distribution of rainfall in the region. The impact of these forecasts on the expectation for the event is not always clear or easily conveyed. This article proposes a technique based on Monte Carlo simulation for adjusting existing climatologic statistical parameters to match forecast information, resulting in new parameters defining the probability of events for the forecast interval. The resulting parameters are shown to approximate the forecasts with reasonable accuracy. To show the value of the technique as an application for seasonal rainfall, it is used with consensus forecast developed for the Greater Horn of Africa for the 2009 March-April-May season. An alternative, analytical approach is also proposed, and discussed in comparison to the first simulation-based technique.

Who Is the Big Spender? Price Index Effects in Comparisons of Educational Expenditures between Countries and Over Time

ERIC Educational Resources Information Center

Arneberg, Marie; Bowitz, Einar

2006-01-01

International comparisons of data on expenditure on education use purchasing power parities for currency conversion and adjustment for price differences between countries to allow for volume comparisons. The resulting indicators are commonly interpreted as differences between countries in input volumes to the education sector-teachers, materials,…

Forecast Verification: Identification of small changes in weather forecasting skill

NASA Astrophysics Data System (ADS)

Weatherhead, E. C.; Jensen, T. L.

2017-12-01

Global and regonal weather forecasts have improved over the past seven decades most often because of small, incrmental improvements. The identificaiton and verification of forecast improvement due to proposed small changes in forecasting can be expensive and, if not carried out efficiently, can slow progress in forecasting development. This presentation will look at the skill of commonly used verification techniques and show how the ability to detect improvements can depend on the magnitude of the improvement, the number of runs used to test the improvement, the location on the Earth and the statistical techniques used. For continuous variables, such as temperture, wind and humidity, the skill of a forecast can be directly compared using a pair-wise statistical test that accommodates the natural autocorrelation and magnitude of variability. For discrete variables, such as tornado outbreaks, or icing events, the challenges is to reduce the false alarm rate while improving the rate of correctly identifying th discrete event. For both continuus and discrete verification results, proper statistical approaches can reduce the number of runs needed to identify a small improvement in forecasting skill. Verification within the Next Generation Global Prediction System is an important component to the many small decisions needed to make stat-of-the-art improvements to weather forecasting capabilities. The comparison of multiple skill scores with often conflicting results requires not only appropriate testing, but also scientific judgment to assure that the choices are appropriate not only for improvements in today's forecasting capabilities, but allow improvements that will come in the future.

EU pharmaceutical expenditure forecast.

PubMed

Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

2014-01-01

With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States' pharmaceutical budgets. This model took into account population ageing, as well as current and future country-specific pricing, reimbursement, and market access policies (the project was performed for the European Commission; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). In order to have a representative heterogeneity of EU Member States, the following countries were selected for the analysis: France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. A forecasting period of 5 years (2012-2016) was chosen to assess the net pharmaceutical budget impact. A model for generics and biosimilars was developed for each country. The model estimated a separate and combined effect of the direct and indirect impacts of the patent cliff. A second model, estimating the sales development and the risk of development failure, was developed for new drugs. New drugs were reviewed individually to assess their clinical potential and translate it into commercial potential. The forecast was carried out according to three perspectives (healthcare public payer, society, and manufacturer), and several types of distribution chains (retail, hospital, and combined retail and hospital). Probabilistic and deterministic sensitivity analyses were carried out. According to the model, all countries experienced drug budget reductions except Poland (+€41 million). Savings were expected to be the highest in the United Kingdom (-€9,367 million), France (-€5,589 million), and, far behind them

EU pharmaceutical expenditure forecast

PubMed Central

Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

2014-01-01

Background and Objectives With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States’ pharmaceutical budgets. This model took into account population ageing, as well as current and future country-specific pricing, reimbursement, and market access policies (the project was performed for the European Commission; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Method In order to have a representative heterogeneity of EU Member States, the following countries were selected for the analysis: France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. A forecasting period of 5 years (2012–2016) was chosen to assess the net pharmaceutical budget impact. A model for generics and biosimilars was developed for each country. The model estimated a separate and combined effect of the direct and indirect impacts of the patent cliff. A second model, estimating the sales development and the risk of development failure, was developed for new drugs. New drugs were reviewed individually to assess their clinical potential and translate it into commercial potential. The forecast was carried out according to three perspectives (healthcare public payer, society, and manufacturer), and several types of distribution chains (retail, hospital, and combined retail and hospital). Probabilistic and deterministic sensitivity analyses were carried out. Results According to the model, all countries experienced drug budget reductions except Poland (+€41 million). Savings were expected to be the highest in the United Kingdom (−€9,367 million), France

Probabilities of Possible Future Prices (Short-Term Energy Outlook Supplement April 2010)

EIA Publications

2010-01-01

The Energy Information Administration introduced a monthly analysis of energy price volatility and forecast uncertainty in the October 2009 Short-Term Energy Outlook (STEO). Included in the analysis were charts portraying confidence intervals around the New York Mercantile Exchange (NYMEX) futures prices of West Texas Intermediate (equivalent to light sweet crude oil) and Henry Hub natural gas contracts.

Monthly stumpage prices for the Pacific Northwest.

Treesearch

Richard W. Haynes

1991-01-01

Seasonal variation is found in monthly stumpage price data. Seasonal adjustments indicate that monthly adjustments improve the utility of estimates of monthly stumpage prices. Comparisons of adjusted and unadjusted prices suggest that the unadjusted price series are reasonably robust.

Modeling and simulation of consumer response to dynamic pricing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valenzuela, J.; Thimmapuram, P.; Kim, J

2012-08-01

Assessing the impacts of dynamic-pricing under the smart grid concept is becoming extremely important for deciding its full deployment. In this paper, we develop a model that represents the response of consumers to dynamic pricing. In the model, consumers use forecasted day-ahead prices to shift daily energy consumption from hours when the price is expected to be high to hours when the price is expected to be low while maintaining the total energy consumption as unchanged. We integrate the consumer response model into the Electricity Market Complex Adaptive System (EMCAS). EMCAS is an agent-based model that simulates restructured electricity markets.more » We explore the impacts of dynamic-pricing on price spikes, peak demand, consumer energy bills, power supplier profits, and congestion costs. A simulation of an 11-node test network that includes eight generation companies and five aggregated consumers is performed for a period of 1 month. In addition, we simulate the Korean power system.« less

Naive vs. Sophisticated Methods of Forecasting Public Library Circulations.

ERIC Educational Resources Information Center

Brooks, Terrence A.

1984-01-01

Two sophisticated--autoregressive integrated moving average (ARIMA), straight-line regression--and two naive--simple average, monthly average--forecasting techniques were used to forecast monthly circulation totals of 34 public libraries. Comparisons of forecasts and actual totals revealed that ARIMA and monthly average methods had smallest mean…

A comparison of alternative methods for measuring cigarette prices.

PubMed

Chaloupka, Frank J; Tauras, John A; Strasser, Julia H; Willis, Gordon; Gibson, James T; Hartman, Anne M

2015-05-01

Government agencies, public health organisations and tobacco control researchers rely on accurate estimates of cigarette prices for a variety of purposes. Since the 1950s, the Tax Burden on Tobacco (TBOT) has served as the most widely used source of this price data despite its limitations. This paper compares the prices and collection methods of the TBOT retail-based data and the 2003 and 2006/2007 waves of the population-based Tobacco Use Supplement to the Current Population Survey (TUS-CPS). From the TUS-CPS, we constructed multiple state-level measures of cigarette prices, including weighted average prices per pack (based on average prices for single-pack purchases and average prices for carton purchases) and compared these with the weighted average price data reported in the TBOT. We also constructed several measures of tax avoidance from the TUS-CPS self-reported data. For the 2003 wave, the average TUS-CPS price was 71 cents per pack less than the average TBOT price; for the 2006/2007 wave, the difference was 47 cents. TUS-CPS and TBOT prices were also significantly different at the state level. However, these differences varied widely by state due to tax avoidance opportunities, such as cross-border purchasing. The TUS-CPS can be used to construct valid measures of cigarette prices. Unlike the TBOT, the TUS-CPS captures the effect of price-reducing marketing strategies, as well as tax avoidance practices and non-traditional types of purchasing. Thus, self-reported data like TUS-CPS appear to have advantages over TBOT in estimating the 'real' price that smokers face. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Valuing year-to-go hydrologic forecast improvements for a peaking hydropower system in the Sierra Nevada

NASA Astrophysics Data System (ADS)

Rheinheimer, David E.; Bales, Roger C.; Oroza, Carlos A.; Lund, Jay R.; Viers, Joshua H.

2016-05-01

We assessed the potential value of hydrologic forecasting improvements for a snow-dominated high-elevation hydropower system in the Sierra Nevada of California, using a hydropower optimization model. To mimic different forecasting skill levels for inflow time series, rest-of-year inflows from regression-based forecasts were blended in different proportions with representative inflows from a spatially distributed hydrologic model. The statistical approach mimics the simpler, historical forecasting approach that is still widely used. Revenue was calculated using historical electricity prices, with perfect price foresight assumed. With current infrastructure and operations, perfect hydrologic forecasts increased annual hydropower revenue by 0.14 to 1.6 million, with lower values in dry years and higher values in wet years, or about $0.8 million (1.2%) on average, representing overall willingness-to-pay for perfect information. A second sensitivity analysis found a wider range of annual revenue gain or loss using different skill levels in snow measurement in the regression-based forecast, mimicking expected declines in skill as the climate warms and historical snow measurements no longer represent current conditions. The value of perfect forecasts was insensitive to storage capacity for small and large reservoirs, relative to average inflow, and modestly sensitive to storage capacity with medium (current) reservoir storage. The value of forecasts was highly sensitive to powerhouse capacity, particularly for the range of capacities in the northern Sierra Nevada. The approach can be extended to multireservoir, multipurpose systems to help guide investments in forecasting.

Impact of high oil prices on freight transportation : modal shift potential in five corridors, executive summary.

DOT National Transportation Integrated Search

2008-10-01

MAJOR FINDINGS : According to U.S. and international forecasts, oil prices could range between a low of $60 to a : high of $160 per barrel through 2020 (in constant 2008 dollars), but the Central Scenario : indicates that oil prices could stabili...

Building a Consensus Forecast for Crude Oil Prices

DTIC Science & Technology

2006-03-01

Middle East ( Cremer , 1991). As the world became dependant on cheap oil found in the Middle East, the underlying market was changing. Initially...governments in an effort to break into the market ( Cremer , 1991). During this time, Middle Eastern countries received a royalty on the oil produced within...their borders. This meant that government revenues were tied to volume, regardless of price ( Cremer , 1991). But in the 1950s the oil companies

A national econometric forecasting model of the dental sector.

PubMed Central

Feldstein, P J; Roehrig, C S

1980-01-01

The Econometric Model of the the Dental Sector forecasts a broad range of dental sector variables, including dental care prices; the amount of care produced and consumed; employment of hygienists, dental assistants, and clericals; hours worked by dentists; dental incomes; and number of dentists. These forecasts are based upon values specified by the user for the various factors which help determine the supply an demand for dental care, such as the size of the population, per capita income, the proportion of the population covered by private dental insurance, the cost of hiring clericals and dental assistants, and relevant government policies. In a test of its reliability, the model forecast dental sector behavior quite accurately for the period 1971 through 1977. PMID:7461974

Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

NASA Astrophysics Data System (ADS)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

Price comparison of high-cost originator medicines in European countries.

PubMed

Vogler, Sabine; Zimmermann, Nina; Babar, Zaheer-Ud-Din

2017-04-01

In recent years, high-cost medicines have increasingly been challenging the public health budget in all countries including high-income economies. In this context, this study aims to survey, analyze and compare prices of medicines that likely contribute to high expenditure for the public payers in high-income countries. We chose the following 16 European countries: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, the Netherlands, Portugal, Sweden, Slovakia, Spain and United Kingdom. The ex-factory price data of 30 medicines in these countries were collected in national databases accessible through the Pharmaceutical Price Information (PPI) service of Gesundheit Österreich GmbH (Austrian Public Health Institute). The ex-factory prices (median) per unit (e.g. per tablet, vial) ranged from 10.67 cent (levodopa + decarboxylase inhibitor) to 17,000 euro (ipilimumab). A total of 53% of the medicines surveyed had a unit ex-factory price (median) above 200 Euro. For two thirds of the medicines, price differences between the highest-priced country and lowest-priced country ranged between 25 and 100%; the remaining medicines, mainly low-priced medicines, had higher price differential, up to 251%. Medicines with unit prices of a few euros or less were medicines for the treatment of diseases in the nervous system (anti-depressants, medicines to treat Parkinson and for the management of neuropathic pain), of obstructive airway diseases and cardio-vascular medicines (lipid modifying agents). High-priced medicines were particularly cancer medicines. Medicine prices of Greece, Hungary, Slovakia and UK were frequently at the lower end, German and Swedish, as well as Danish and Irish prices at the upper end. For high-priced medicines, actual paid prices are likely to be lower due to confidential discounts and similar funding arrangements between industry and public payers. Pricing authorities refer to the higher undiscounted prices when they use

Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

NASA Astrophysics Data System (ADS)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

How much are you prepared to PAY for a forecast?

NASA Astrophysics Data System (ADS)

Arnal, Louise; Coughlan, Erin; Ramos, Maria-Helena; Pappenberger, Florian; Wetterhall, Fredrik; Bachofen, Carina; van Andel, Schalk Jan

2015-04-01

Probabilistic hydro-meteorological forecasts are a crucial element of the decision-making chain in the field of flood prevention. The operational use of probabilistic forecasts is increasingly promoted through the development of new novel state-of-the-art forecast methods and numerical skill is continuously increasing. However, the value of such forecasts for flood early-warning systems is a topic of diverging opinions. Indeed, the word value, when applied to flood forecasting, is multifaceted. It refers, not only to the raw cost of acquiring and maintaining a probabilistic forecasting system (in terms of human and financial resources, data volume and computational time), but also and most importantly perhaps, to the use of such products. This game aims at investigating this point. It is a willingness to pay game, embedded in a risk-based decision-making experiment. Based on a ``Red Cross/Red Crescent, Climate Centre'' game, it is a contribution to the international Hydrologic Ensemble Prediction Experiment (HEPEX). A limited number of probabilistic forecasts will be auctioned to the participants; the price of these forecasts being market driven. All participants (irrespective of having bought or not a forecast set) will then be taken through a decision-making process to issue warnings for extreme rainfall. This game will promote discussions around the topic of the value of forecasts for decision-making in the field of flood prevention.

Modelling world gold prices and USD foreign exchange relationship using multivariate GARCH model

NASA Astrophysics Data System (ADS)

Ping, Pung Yean; Ahmad, Maizah Hura Binti

2014-12-01

World gold price is a popular investment commodity. The series have often been modeled using univariate models. The objective of this paper is to show that there is a co-movement between gold price and USD foreign exchange rate. Using the effect of the USD foreign exchange rate on the gold price, a model that can be used to forecast future gold prices is developed. For this purpose, the current paper proposes a multivariate GARCH (Bivariate GARCH) model. Using daily prices of both series from 01.01.2000 to 05.05.2014, a causal relation between the two series understudied are found and a bivariate GARCH model is produced.

48 CFR 570.110 - Cost or pricing data and information other than cost or pricing data.

Code of Federal Regulations, 2013 CFR

2013-10-01

... competition. For price analysis of offered rental rates, the contracting officer may use a market survey, an... comparison, or other relevant market research data. For price analysis of offered tenant improvement costs...

48 CFR 570.110 - Cost or pricing data and information other than cost or pricing data.

Code of Federal Regulations, 2014 CFR

2014-10-01

... competition. For price analysis of offered rental rates, the contracting officer may use a market survey, an... comparison, or other relevant market research data. For price analysis of offered tenant improvement costs...

48 CFR 570.110 - Cost or pricing data and information other than cost or pricing data.

Code of Federal Regulations, 2011 CFR

2011-10-01

... competition. For price analysis of offered rental rates, the contracting officer may use a market survey, an... comparison, or other relevant market research data. For price analysis of offered tenant improvement costs...

19 CFR 351.414 - Comparison of normal value with export price (constructed export price).

Code of Federal Regulations, 2010 CFR

2010-04-01

... export price). (a) Introduction. The Secretary normally will average prices used as the basis for normal... calculate weighted averages for such shorter period as the Secretary deems appropriate. (e) Application of...

Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

NASA Astrophysics Data System (ADS)

Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

2012-04-01

In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological

A quantitative comparison of precipitation forecasts between the storm-scale numerical weather prediction model and auto-nowcast system in Jiangsu, China

NASA Astrophysics Data System (ADS)

Wang, Gaili; Yang, Ji; Wang, Dan; Liu, Liping

2016-11-01

Extrapolation techniques and storm-scale Numerical Weather Prediction (NWP) models are two primary approaches for short-term precipitation forecasts. The primary objective of this study is to verify precipitation forecasts and compare the performances of two nowcasting schemes: a Beijing Auto-Nowcast system (BJ-ANC) based on extrapolation techniques and a storm-scale NWP model called the Advanced Regional Prediction System (ARPS). The verification and comparison takes into account six heavy precipitation events that occurred in the summer of 2014 and 2015 in Jiangsu, China. The forecast performances of the two schemes were evaluated for the next 6 h at 1-h intervals using gridpoint-based measures of critical success index, bias, index of agreement, root mean square error, and using an object-based verification method called Structure-Amplitude-Location (SAL) score. Regarding gridpoint-based measures, BJ-ANC outperforms ARPS at first, but then the forecast accuracy decreases rapidly with lead time and performs worse than ARPS after 4-5 h of the initial forecast. Regarding the object-based verification method, most forecasts produced by BJ-ANC focus on the center of the diagram at the 1-h lead time and indicate high-quality forecasts. As the lead time increases, BJ-ANC overestimates precipitation amount and produces widespread precipitation, especially at a 6-h lead time. The ARPS model overestimates precipitation at all lead times, particularly at first.

Forecasting, Forecasting

Treesearch

Michael A. Fosberg

1987-01-01

Future improvements in the meteorological forecasts used in fire management will come from improvements in three areas: observational systems, forecast techniques, and postprocessing of forecasts and better integration of this information into the fire management process.

Time series ARIMA models for daily price of palm oil

NASA Astrophysics Data System (ADS)

Ariff, Noratiqah Mohd; Zamhawari, Nor Hashimah; Bakar, Mohd Aftar Abu

2015-02-01

Palm oil is deemed as one of the most important commodity that forms the economic backbone of Malaysia. Modeling and forecasting the daily price of palm oil is of great interest for Malaysia's economic growth. In this study, time series ARIMA models are used to fit the daily price of palm oil. The Akaike Infromation Criterion (AIC), Akaike Infromation Criterion with a correction for finite sample sizes (AICc) and Bayesian Information Criterion (BIC) are used to compare between different ARIMA models being considered. It is found that ARIMA(1,2,1) model is suitable for daily price of crude palm oil in Malaysia for the year 2010 to 2012.

Comparison of Dst Forecast Models for Intense Geomagnetic Storms

NASA Technical Reports Server (NTRS)

Ji, Eun-Young; Moon, Y.-J.; Gopalswamy, N.; Lee, D.-H.

2012-01-01

We have compared six disturbance storm time (Dst) forecast models using 63 intense geomagnetic storms (Dst <=100 nT) that occurred from 1998 to 2006. For comparison, we estimated linear correlation coefficients and RMS errors between the observed Dst data and the predicted Dst during the geomagnetic storm period as well as the difference of the value of minimum Dst (Delta Dst(sub min)) and the difference in the absolute value of Dst minimum time (Delta t(sub Dst)) between the observed and the predicted. As a result, we found that the model by Temerin and Li gives the best prediction for all parameters when all 63 events are considered. The model gives the average values: the linear correlation coefficient of 0.94, the RMS error of 14.8 nT, the Delta Dst(sub min) of 7.7 nT, and the absolute value of Delta t(sub Dst) of 1.5 hour. For further comparison, we classified the storm events into two groups according to the magnitude of Dst. We found that the model of Temerin and Lee is better than the other models for the events having 100 <= Dst < 200 nT, and three recent models (the model of Wang et al., the model of Temerin and Li, and the model of Boynton et al.) are better than the other three models for the events having Dst <= 200 nT.

Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

NASA Astrophysics Data System (ADS)

Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

2017-04-01

The improvement of a forecasting system and the evaluation of the quality of its forecasts are recurrent steps in operational practice. However, the evaluation of forecast value or forecast usefulness for better decision-making is, to our knowledge, less frequent, even if it might be essential in many sectors such as hydropower and flood warning. In the hydropower sector, forecast value can be quantified by the economic gain obtained with the optimization of operations or reservoir management rules. Several hydropower operational systems use medium-range forecasts (up to 7-10 days ahead) and energy price predictions to optimize hydropower production. Hence, the operation of hydropower systems, including the management of water in reservoirs, is impacted by weather, climate and hydrologic variability as well as extreme events. In order to assess how the quality of hydrometeorological forecasts impact operations, it is essential to first understand if and how operations and management rules are sensitive to input predictions of different quality. This study investigates how 7-day ahead deterministic and ensemble streamflow forecasts of different quality might impact the economic gains of energy production. It is based on a research model developed by Irstea and EDF to investigate issues relevant to the links between quality and value of forecasts in the optimisation of energy production at the short range. Based on streamflow forecasts and pre-defined management constraints, the model defines the best hours (i.e., the hours with high energy prices) to produce electricity. To highlight the link between forecasts quality and their economic value, we built several synthetic ensemble forecasts based on observed streamflow time series. These inputs are generated in a controlled environment in order to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts are used to assess the sensitivity of the decision model to forecast quality

76 FR 9696 - Equipment Price Forecasting in Energy Conservation Standards Analysis

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-22

... for particular efficiency design options, an empirical experience curve fit to the available data may be used to forecast future costs of such design option technologies. If a statistical evaluation indicates a low level of confidence in estimates of the design option cost trend, this method should not be...

Enhancing medicine price transparency through price information mechanisms

PubMed Central

2014-01-01

Background Medicine price information mechanisms provide an essential tool to countries that seek a better understanding of product availability, market prices and price compositions of individual medicines. To be effective and contribute to cost savings, these mechanisms need to consider prices in their particular contexts when comparing between countries. This article discusses in what ways medicine price information mechanisms can contribute to increased price transparency and how this may affect access to medicines for developing countries. Methods We used data collected during the course of a WHO project focusing on the development of a vaccine price and procurement information mechanism. The project collected information from six medicine price information mechanisms and interviewed data managers and technical experts on key aspects as well as observed market effects of these mechanisms. The reviewed mechanisms were broken down into categories including objective and target audience, as well as the sources, types and volumes of data included. Information provided by the mechanisms was reviewed according to data available on medicine prices, product characteristics, and procurement modalities. Results We found indications of positive effects on access to medicines resulting from the utilization of the reviewed mechanisms. These include the uptake of higher quality medicines, more favorable results from contract negotiations, changes in national pricing policies, and the decrease of prices in certain segments for countries participating in or deriving data from the various mechanisms. Conclusion The reviewed mechanisms avoid the methodological challenges observed for medicine price comparisons that only use national price databases. They work with high quality data and display prices in the appropriate context of procurement modalities as well as the peculiarities of purchasing countries. Medicine price information mechanisms respond to the need for increased

Enhancing medicine price transparency through price information mechanisms.

PubMed

Hinsch, Michael; Kaddar, Miloud; Schmitt, Sarah

2014-05-08

Medicine price information mechanisms provide an essential tool to countries that seek a better understanding of product availability, market prices and price compositions of individual medicines. To be effective and contribute to cost savings, these mechanisms need to consider prices in their particular contexts when comparing between countries. This article discusses in what ways medicine price information mechanisms can contribute to increased price transparency and how this may affect access to medicines for developing countries. We used data collected during the course of a WHO project focusing on the development of a vaccine price and procurement information mechanism. The project collected information from six medicine price information mechanisms and interviewed data managers and technical experts on key aspects as well as observed market effects of these mechanisms.The reviewed mechanisms were broken down into categories including objective and target audience, as well as the sources, types and volumes of data included. Information provided by the mechanisms was reviewed according to data available on medicine prices, product characteristics, and procurement modalities. We found indications of positive effects on access to medicines resulting from the utilization of the reviewed mechanisms. These include the uptake of higher quality medicines, more favorable results from contract negotiations, changes in national pricing policies, and the decrease of prices in certain segments for countries participating in or deriving data from the various mechanisms. The reviewed mechanisms avoid the methodological challenges observed for medicine price comparisons that only use national price databases. They work with high quality data and display prices in the appropriate context of procurement modalities as well as the peculiarities of purchasing countries. Medicine price information mechanisms respond to the need for increased medicine price transparency and have the

A Comparison of the Performance of Advanced Statistical Techniques for the Refinement of Day-ahead and Longer NWP-based Wind Power Forecasts

NASA Astrophysics Data System (ADS)

Zack, J. W.

2015-12-01

Predictions from Numerical Weather Prediction (NWP) models are the foundation for wind power forecasts for day-ahead and longer forecast horizons. The NWP models directly produce three-dimensional wind forecasts on their respective computational grids. These can be interpolated to the location and time of interest. However, these direct predictions typically contain significant systematic errors ("biases"). This is due to a variety of factors including the limited space-time resolution of the NWP models and shortcomings in the model's representation of physical processes. It has become common practice to attempt to improve the raw NWP forecasts by statistically adjusting them through a procedure that is widely known as Model Output Statistics (MOS). The challenge is to identify complex patterns of systematic errors and then use this knowledge to adjust the NWP predictions. The MOS-based improvements are the basis for much of the value added by commercial wind power forecast providers. There are an enormous number of statistical approaches that can be used to generate the MOS adjustments to the raw NWP forecasts. In order to obtain insight into the potential value of some of the newer and more sophisticated statistical techniques often referred to as "machine learning methods" a MOS-method comparison experiment has been performed for wind power generation facilities in 6 wind resource areas of California. The underlying NWP models that provided the raw forecasts were the two primary operational models of the US National Weather Service: the GFS and NAM models. The focus was on 1- and 2-day ahead forecasts of the hourly wind-based generation. The statistical methods evaluated included: (1) screening multiple linear regression, which served as a baseline method, (2) artificial neural networks, (3) a decision-tree approach called random forests, (4) gradient boosted regression based upon an decision-tree algorithm, (5) support vector regression and (6) analog ensemble

Annual Energy Outlook 2013 with Projections to 2040

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

The Annual Energy Outlook 2013 (AEO2013), prepared by the U.S. Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2040, based on results from EIA’s National Energy Modeling System. The report begins with an “Executive summary” that highlights key aspects of the projections. It is followed by a “Legislation and regulations” section that discusses evolving legislative and regulatory issues, including a summary of recently enacted legislation and regulations, such as: Updated handling of the U.S. Environmental Protection Agency’s (EPA) National Emissions Standards for Hazardous Air Pollutants for industrial boilers and process heaters; New light-duty vehiclemore » (LDV) greenhouse gas (GHG) and corporate average fuel economy (CAFE) standards for model years 2017 to 2025; Reinstatement of the Clean Air Interstate Rule (CAIR) after the court’s announcement of intent to vacate the Cross-State Air Pollution Rule (CSAPR); and Modeling of California’s Assembly Bill 32, the Global Warming Solutions Act (AB 32), which allows for representation of a cap-and-trade program developed as part of California’s GHG reduction goals for 2020. The “Issues in focus” section contains discussions of selected energy topics, including a discussion of the results in two cases that adopt different assumptions about the future course of existing policies, with one case assuming the elimination of sunset provisions in existing policies and the other case assuming the elimination of the sunset provisions and the extension of a selected group of existing public policies—CAFE standards, appliance standards, and production tax credits. Other discussions include: oil price and production trends in AEO2013; U.S. reliance on imported liquids under a range of cases; competition between coal and natural gas in electric power generation; high and low nuclear scenarios through 2040; and the impact of growth in

Application of Neural Network Technologies for Price Forecasting in the Liberalized Electricity Market

NASA Astrophysics Data System (ADS)

Gerikh, Valentin; Kolosok, Irina; Kurbatsky, Victor; Tomin, Nikita

2009-01-01

The paper presents the results of experimental studies concerning calculation of electricity prices in different price zones in Russia and Europe. The calculations are based on the intelligent software "ANAPRO" that implements the approaches based on the modern methods of data analysis and artificial intelligence technologies.

Dynamic pricing of network goods with boundedly rational consumers.

PubMed

Radner, Roy; Radunskaya, Ami; Sundararajan, Arun

2014-01-07

We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller's optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product's user base evolving over time and consumers basing their choices on a mixture of a myopic and a "stubborn" expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice.

Dynamic pricing of network goods with boundedly rational consumers

PubMed Central

Radner, Roy; Radunskaya, Ami; Sundararajan, Arun

2014-01-01

We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller’s optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product’s user base evolving over time and consumers basing their choices on a mixture of a myopic and a “stubborn” expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice. PMID:24367101

Generalized networking engineering: optimal pricing and routing in multiservice networks

NASA Astrophysics Data System (ADS)

Mitra, Debasis; Wang, Qiong

2002-07-01

One of the functions of network engineering is to allocate resources optimally to forecasted demand. We generalize the mechanism by incorporating price-demand relationships into the problem formulation, and optimizing pricing and routing jointly to maximize total revenue. We consider a network, with fixed topology and link bandwidths, that offers multiple services, such as voice and data, each having characteristic price elasticity of demand, and quality of service and policy requirements on routing. Prices, which depend on service type and origin-destination, determine demands, that are routed, subject to their constraints, so as to maximize revenue. We study the basic properties of the optimal solution and prove that link shadow costs provide the basis for both optimal prices and optimal routing policies. We investigate the impact of input parameters, such as link capacities and price elasticities, on prices, demand growth, and routing policies. Asymptotic analyses, in which network bandwidth is scaled to grow, give results that are noteworthy for their qualitative insights. Several numerical examples illustrate the analyses.

What factors affect the prices of low-priced U.S. solar PV systems?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nemet, Gregory F.; O'Shaughnessy, Eric; Wiser, Ryan

The price of solar PV systems has declined rapidly, yet there are some much lower-priced systems than others. This study explores the factors that determine prices in these low-priced (LP) systems. Using a data set of 42,611 residential-scale PV systems installed in the U.S. in 2013, we use quantile regressions to estimate the importance of factors affecting the installed prices for LP systems (those at the 10th percentile) in comparison to median-priced systems. We find that the value of solar to consumers-a variable that accounts for subsidies, electric rates, and PV generation levels-is associated with lower prices for LP systemsmore » but higher prices for median priced systems. Conversely, systems installed in new home construction are associated with lower prices at the median but higher prices for LP. Other variables have larger price-reducing effects on LP than on median priced systems: systems installed in Arizona and Florida, as well as commercial and thin film systems. In contrast, the following have a smaller effect on prices for LP systems than median priced systems: tracking systems, self-installations, systems installed in Massachusetts, the system size, and installer experience. Furthermore, these results highlight the complex factors at play that lead to LP systems and shed light into how such LP systems can come about.« less

What factors affect the prices of low-priced U.S. solar PV systems?

DOE PAGES

Nemet, Gregory F.; O'Shaughnessy, Eric; Wiser, Ryan; ...

2017-08-09

The price of solar PV systems has declined rapidly, yet there are some much lower-priced systems than others. This study explores the factors that determine prices in these low-priced (LP) systems. Using a data set of 42,611 residential-scale PV systems installed in the U.S. in 2013, we use quantile regressions to estimate the importance of factors affecting the installed prices for LP systems (those at the 10th percentile) in comparison to median-priced systems. We find that the value of solar to consumers-a variable that accounts for subsidies, electric rates, and PV generation levels-is associated with lower prices for LP systemsmore » but higher prices for median priced systems. Conversely, systems installed in new home construction are associated with lower prices at the median but higher prices for LP. Other variables have larger price-reducing effects on LP than on median priced systems: systems installed in Arizona and Florida, as well as commercial and thin film systems. In contrast, the following have a smaller effect on prices for LP systems than median priced systems: tracking systems, self-installations, systems installed in Massachusetts, the system size, and installer experience. Furthermore, these results highlight the complex factors at play that lead to LP systems and shed light into how such LP systems can come about.« less

Assistive technology pricing in Australia: is it efficient and equitable?

PubMed

Summers, Michael P; Verikios, George

2018-02-01

Objective To examine available systematically collected evidence regarding prices for assistive technology (AT; e.g. disability aids and equipment) in Australia with other comparable countries. Issues of appropriate AT pricing are coming to the fore as a consequence of efforts to move to consumer-centric purchasing decisions with the National Disability Insurance Scheme (NDIS) and also in the recent aged care reforms. Methods We identified and present three sets of AT price comparisons. Two comparisons were based solely on the lowest prices advertised on the internet, and one comparison examined recommended retail prices. Variables essential to ensuring accurate comparisons, as well as significant supply-chain issues were also examined and considered in the analyses. Results The first internet-only price comparison found that overall AT prices were 38% higher in Australia compared to other countries, but did not factor in shipping and other related costs that are essential to include given that most AT is imported. The second internet-only price comparison found that overall Australian prices were 24% lower when shipping and related costs were included. The recommended retail price comparisons found that Australian prices were between 14% and 27% lower. Prices for internet-only retailers (those with no bricks-and-mortar presence) are consistently lower for all products than those sold by retailers with actual shop-fronts. Further, there is no evidence of suppliers earning supranormal profits in Australia. Conclusions The results indicate that AT prices in Australia are efficient and equitable, with no significant indicators of market failure which would require government intervention. Efforts to reduce prices through the excessive use of large-scale government procurement programs are likely to reduce diversity and innovation in AT and raise AT prices over time. Open markets and competition with centralised tracking of purchases and providers to minimise possible

A comparison of model short-range forecasts and the ARM Microbase data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hnilo, J J

2006-09-22

For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the 'Microbase' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averagedmore » to 3hourly data for direct comparison to our model output.« less

Artificial neural network model of the hybrid EGARCH volatility of the Taiwan stock index option prices

NASA Astrophysics Data System (ADS)

Tseng, Chih-Hsiung; Cheng, Sheng-Tzong; Wang, Yi-Hsien; Peng, Jin-Tang

2008-05-01

This investigation integrates a novel hybrid asymmetric volatility approach into an Artificial Neural Networks option-pricing model to upgrade the forecasting ability of the price of derivative securities. The use of the new hybrid asymmetric volatility method can simultaneously decrease the stochastic and nonlinearity of the error term sequence, and capture the asymmetric volatility. Therefore, analytical results of the ANNS option-pricing model reveal that Grey-EGARCH volatility provides greater predictability than other volatility approaches.

What Factors Affect the Prices of Low-Priced U.S. Solar PV Systems?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nemet, Gregory F.; O'Shaughnessy, Eric; Wiser, Ryan

The price of solar PV systems has declined rapidly, yet there are some much lower-priced systems than others. This study explores the factors leading some systems to be so much lower priced than others. Using a data set of 42,611 residential-scale PV systems installed in the U.S. in 2013, we use quantile regressions to estimate the importance of factors affecting the installed prices for low-priced (LP) systems (those at the 10th percentile) in comparison to median-priced systems. We find that the value of solar to consumers–a variable that accounts for subsidies, electric rates, and PV generation levels–is associated with lowermore » prices for LP systems but higher prices for median priced systems. Conversely, systems installed in new home construction are associated with lower prices at the median but higher prices for LP. Other variables have larger cost-reducing effects on LP than on median priced systems: systems installed in Arizona and Florida, as well as commercial and thin film systems. In contrast, the following have a smaller effect on prices for LP systems than median priced systems: tracking systems, self-installations, systems installed in Massachusetts, the system size, and installer experience. These results highlight the complex factors at play that lead to LP systems and shed light into how such LP systems can come about.« less

Enterprise systems in financial sector - an application in precious metal trading forecasting

NASA Astrophysics Data System (ADS)

Chen, Xiaozhu; Fang, Yiwei

2013-11-01

The use of enterprise systems has become increasingly popular in the financial service industry. This paper discusses the applications of enterprise systems in the financial sectors and presents an application in gold price forecasting. We carefully examine the impacts of a few most widely assumed factors that have significant impact on the long-term gold price using statistical regression techniques. The analysis on our proposed linear regression mode indicates that the United States ultra scale of M2 money supply has been the most important catalyst for the rising price of gold, and the CRB index upward trend has also been the weighty factor for pushing up the gold price. In addition, the gold price has a low negative correlation with the Dow Jones Industrial Average, and low positive correlations with the US dollar index and the gold ETFs holdings.

Hydro-economic assessment of hydrological forecasting systems

NASA Astrophysics Data System (ADS)

Boucher, M.-A.; Tremblay, D.; Delorme, L.; Perreault, L.; Anctil, F.

2012-01-01

SummaryAn increasing number of publications show that ensemble hydrological forecasts exhibit good performance when compared to observed streamflow. Many studies also conclude that ensemble forecasts lead to a better performance than deterministic ones. This investigation takes one step further by not only comparing ensemble and deterministic forecasts to observed values, but by employing the forecasts in a stochastic decision-making assistance tool for hydroelectricity production, during a flood event on the Gatineau River in Canada. This allows the comparison between different types of forecasts according to their value in terms of energy, spillage and storage in a reservoir. The motivation for this is to adopt the point of view of an end-user, here a hydroelectricity production society. We show that ensemble forecasts exhibit excellent performances when compared to observations and are also satisfying when involved in operation management for electricity production. Further improvement in terms of productivity can be reached through the use of a simple post-processing method.

Three essays on agricultural price volatility and the linkages between agricultural and energy markets

NASA Astrophysics Data System (ADS)

Wu, Feng

This dissertation contains three essays. In the first essay I use a volatility spillover model to find evidence of significant spillovers from crude oil prices to corn cash and futures prices, and that these spillover effects are time-varying. Results reveal that corn markets have become much more connected to crude oil markets after the introduction of the Energy Policy Act of 2005. Furthermore, crude oil prices transmit positive volatility spillovers into corn prices and movements in corn prices become more energy-driven as the ethanol gasoline consumption ratio increases. Based on this strong volatility link between crude oil and corn prices, a new cross hedging strategy for managing corn price risk using oil futures is examined and its performance studied. Results show that this cross hedging strategy provides only slightly better hedging performance compared to traditional hedging in corn futures markets alone. The implication is that hedging corn price risk in corn futures markets alone can still provide relatively satisfactory performance in the biofuel era. The second essay studies the spillover effect of biofuel policy on participation in the Conservation Reserve Program. Landowners' participation decisions are modeled using a real options framework. A novel aspect of the model is that it captures the structural change in agriculture caused by rising biofuel production. The resulting model is used to simulate the spillover effect under various conditions. In particular, I simulate how increased growth in agricultural returns, persistence of the biofuel production boom, and the volatility surrounding agricultural returns, affect conservation program participation decisions. Policy implications of these results are also discussed. The third essay proposes a methodology to construct a risk-adjusted implied volatility measure that removes the forecasting bias of the model-free implied volatility measure. The risk adjustment is based on a closed

STATUS AND PROGRESS IN PARTICULATE MATTER FORECASTING: INITIAL APPLICATION OF THE ETA- CMAQ FORECAST MODEL

EPA Science Inventory

This presentation reviews the status and progress in forecasting particulate matter distributions. The shortcomings in representation of particulate matter formation in current atmospheric chemistry/transport models are presented based on analyses and detailed comparisons with me...

Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

NASA Technical Reports Server (NTRS)

Watson, Leela R.; Hoeth, Brian; Blottman, Peter F.

2007-01-01

Mesoscale weather conditions can significantly affect the space launch and landing operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). During the summer months, land-sea interactions that occur across KSC and CCAFS lead to the formation of a sea breeze, which can then spawn deep convection. These convective processes often last 60 minutes or less and pose a significant challenge to the forecasters at the National Weather Service (NWS) Spaceflight Meteorology Group (SMG). The main challenge is that a "GO" forecast for thunderstorms and precipitation at the Shuttle Landing Facility is required at the 90 minute deorbit decision for End Of Mission (EOM) and at the 30 minute Return To Launch Site (RTLS) decision. Convective initiation, timing, and mode also present a forecast challenge for the NWS in Melbourne, FL (MLB). The NWS MLB issues such tactical forecast information as Terminal Aerodrome Forecasts (TAF5), Spot Forecasts for fire weather and hazardous materials incident support, and severe/hazardous weather Watches, Warnings, and Advisories. Lastly, these forecasting challenges can also affect the 45th Weather Squadron (45 WS), which provides comprehensive weather forecasts for shuttle launch, as well as ground operations, at KSC and CCAFS. The need for accurate mesoscale model forecasts to aid in their decision making is crucial. This study specifically addresses the skill of different model configurations in forecasting warm season convective initiation. Numerous factors influence the development of convection over the Florida peninsula. These factors include sea breezes, river and lake breezes, the prevailing low-level flow, and convergent flow due to convex coastlines that enhance the sea breeze. The interaction of these processes produces the warm season convective patterns seen over the Florida peninsula. However, warm season convection remains one of the most poorly forecast meteorological parameters. To determine which

How is the weather? Forecasting inpatient glycemic control

PubMed Central

Saulnier, George E; Castro, Janna C; Cook, Curtiss B; Thompson, Bithika M

2017-01-01

Aim: Apply methods of damped trend analysis to forecast inpatient glycemic control. Method: Observed and calculated point-of-care blood glucose data trends were determined over 62 weeks. Mean absolute percent error was used to calculate differences between observed and forecasted values. Comparisons were drawn between model results and linear regression forecasting. Results: The forecasted mean glucose trends observed during the first 24 and 48 weeks of projections compared favorably to the results provided by linear regression forecasting. However, in some scenarios, the damped trend method changed inferences compared with linear regression. In all scenarios, mean absolute percent error values remained below the 10% accepted by demand industries. Conclusion: Results indicate that forecasting methods historically applied within demand industries can project future inpatient glycemic control. Additional study is needed to determine if forecasting is useful in the analyses of other glucometric parameters and, if so, how to apply the techniques to quality improvement. PMID:29134125

Understanding Price Formation in Electricity Markets

NASA Astrophysics Data System (ADS)

Kadoya, Toshihisa; Sasaki, Tetsuo; Yokoyama, Akihiko; Ihara, Satoru

The electricity price will influence the future growth and mix of generation capacity that will in turn influence the future electricity price, and therefore, it is important to understand how electricity price is formed as well as its short-term and long-term impacts on the economy. This paper describes evaluation of PJM day-ahead market bidding data and comparison of various electricity markets in terms of the market clearing price and volatility. The objective is to find critical factors and mechanisms determining the movements of electricity price. It was found that speculation by a small number of bidders can cause price spikes, that a Nash equilibrium may exist during a delayed response of the electricity price to a decline of the fuel price, and that the hydro generation with storage capability effectively stabilizes the electricity price.

40 CFR 30.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-07-01

... UNIFORM ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

38 CFR 49.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-07-01

...) UNIFORM ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

32 CFR 32.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-07-01

... REGULATIONS ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

36 CFR 1210.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-07-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards... in various ways, including the comparison of price quotations submitted, market prices and similar...

38 CFR 49.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-07-01

...) UNIFORM ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

36 CFR 1210.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-07-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards... in various ways, including the comparison of price quotations submitted, market prices and similar...

40 CFR 30.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-07-01

... UNIFORM ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

32 CFR 32.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-07-01

... REGULATIONS ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

32 CFR 32.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-07-01

... REGULATIONS ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

32 CFR 32.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-07-01

... REGULATIONS ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

40 CFR 30.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-07-01

... UNIFORM ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

40 CFR 30.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-07-01

... UNIFORM ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

38 CFR 49.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) UNIFORM ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

38 CFR 49.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) UNIFORM ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

36 CFR 1210.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-07-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards... in various ways, including the comparison of price quotations submitted, market prices and similar...

Determination of sample size for higher volatile data using new framework of Box-Jenkins model with GARCH: A case study on gold price

NASA Astrophysics Data System (ADS)

Roslindar Yaziz, Siti; Zakaria, Roslinazairimah; Hura Ahmad, Maizah

2017-09-01

The model of Box-Jenkins - GARCH has been shown to be a promising tool for forecasting higher volatile time series. In this study, the framework of determining the optimal sample size using Box-Jenkins model with GARCH is proposed for practical application in analysing and forecasting higher volatile data. The proposed framework is employed to daily world gold price series from year 1971 to 2013. The data is divided into 12 different sample sizes (from 30 to 10200). Each sample is tested using different combination of the hybrid Box-Jenkins - GARCH model. Our study shows that the optimal sample size to forecast gold price using the framework of the hybrid model is 1250 data of 5-year sample. Hence, the empirical results of model selection criteria and 1-step-ahead forecasting evaluations suggest that the latest 12.25% (5-year data) of 10200 data is sufficient enough to be employed in the model of Box-Jenkins - GARCH with similar forecasting performance as by using 41-year data.

NCEP Air Quality Forecast(AQF) Graphics

Science.gov Websites

Forecasts CMAQ PM Bias Corr. Forecasts Change Plot Type: Comparison plots Difference plots Year: 2018 2017 2016 2015 Month: Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Day: 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Select Cycle: 06Z 12Z Select Region

A Feature Fusion Based Forecasting Model for Financial Time Series

PubMed Central

Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

2014-01-01

Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models. PMID:24971455

Price dynamics in political prediction markets

PubMed Central

Majumder, Saikat Ray; Diermeier, Daniel; Rietz, Thomas A.; Amaral, Luís A. Nunes

2009-01-01

Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election “winner-takes-all” markets. As with other financial markets, we find uncorrelated returns, power-law decaying volatility correlations, and, usually, power-law decaying distributions of returns. However, unlike other financial markets, we find conditional diverging volatilities as the contract settlement date approaches. We propose a dynamic binary option model that captures all features of the empirical data and can potentially provide a tool with which one may extract true information events from a price time series. PMID:19155442

45 CFR 74.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-10-01

... REQUIREMENTS FOR AWARDS AND SUBAWARDS TO INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NONPROFIT... comparison of price quotations submitted, market prices and similar indicia, together with discounts. Cost...

28 CFR 70.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-07-01

... GRANTS AND AGREEMENTS (INCLUDING SUBAWARDS) WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS AND OTHER... comparison of price quotations submitted, market prices and similar indicia, together with discounts. Cost...

22 CFR 145.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards § 145... ways, including the comparison of price quotations submitted, market prices and similar indicia...

24 CFR 84.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards § 84... ways, including the comparison of price quotations submitted, market prices and similar indicia...

24 CFR 84.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards § 84... ways, including the comparison of price quotations submitted, market prices and similar indicia...

28 CFR 70.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-07-01

... GRANTS AND AGREEMENTS (INCLUDING SUBAWARDS) WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS AND OTHER... comparison of price quotations submitted, market prices and similar indicia, together with discounts. Cost...

7 CFR 3019.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

22 CFR 145.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards § 145... ways, including the comparison of price quotations submitted, market prices and similar indicia...

24 CFR 84.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards § 84... ways, including the comparison of price quotations submitted, market prices and similar indicia...

45 CFR 74.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-10-01

... REQUIREMENTS FOR AWARDS AND SUBAWARDS TO INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NONPROFIT... comparison of price quotations submitted, market prices and similar indicia, together with discounts. Cost...

22 CFR 145.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards § 145... ways, including the comparison of price quotations submitted, market prices and similar indicia...

7 CFR 3019.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

... HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

22 CFR 145.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards § 145... ways, including the comparison of price quotations submitted, market prices and similar indicia...

45 CFR 74.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-10-01

... REQUIREMENTS FOR AWARDS AND SUBAWARDS TO INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NONPROFIT... comparison of price quotations submitted, market prices and similar indicia, together with discounts. Cost...

28 CFR 70.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-07-01

... GRANTS AND AGREEMENTS (INCLUDING SUBAWARDS) WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS AND OTHER... comparison of price quotations submitted, market prices and similar indicia, together with discounts. Cost...

28 CFR 70.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-07-01

... GRANTS AND AGREEMENTS (INCLUDING SUBAWARDS) WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS AND OTHER... comparison of price quotations submitted, market prices and similar indicia, together with discounts. Cost...

7 CFR 3019.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

24 CFR 84.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement Standards § 84... ways, including the comparison of price quotations submitted, market prices and similar indicia...

2 CFR 215.45 - Cost and price analysis.

Code of Federal Regulations, 2010 CFR

2010-01-01

... ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER... ways, including the comparison of price quotations submitted, market prices and similar indicia...

Price elasticity matrix of demand in power system considering demand response programs

NASA Astrophysics Data System (ADS)

Qu, Xinyao; Hui, Hongxun; Yang, Shengchun; Li, Yaping; Ding, Yi

2018-02-01

The increasing renewable energy power generations have brought more intermittency and volatility to the electric power system. Demand-side resources can improve the consumption of renewable energy by demand response (DR), which becomes one of the important means to improve the reliability of power system. In price-based DR, the sensitivity analysis of customer’s power demand to the changing electricity prices is pivotal for setting reasonable prices and forecasting loads of power system. This paper studies the price elasticity matrix of demand (PEMD). An improved PEMD model is proposed based on elasticity effect weight, which can unify the rigid loads and flexible loads. Moreover, the structure of PEMD, which is decided by price policies and load types, and the calculation method of PEMD are also proposed. Several cases are studied to prove the effectiveness of this method.

36 CFR 1210.45 - Cost and price analysis.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Cost and price analysis. 1210.45 Section 1210.45 Parks, Forests, and Public Property NATIONAL ARCHIVES AND RECORDS ADMINISTRATION... in various ways, including the comparison of price quotations submitted, market prices and similar...

Forecasting forecast skill

NASA Technical Reports Server (NTRS)

Kalnay, Eugenia; Dalcher, Amnon

1987-01-01

It is shown that it is possible to predict the skill of numerical weather forecasts - a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average correlation) between members of an ensemble of forecasts started from five different analyses. The analyses had been previously derived for satellite-data-impact studies and included, in the Northern Hemisphere, moderate perturbations associated with the use of different observing systems. When the Northern Hemisphere was used as a verification region, the prediction of skill was rather poor. This is due to the fact that such a large area usually contains regions with excellent forecasts as well as regions with poor forecasts, and does not allow for discrimination between them. However, when regional verifications were used, the ensemble forecast dispersion provided a very good prediction of the quality of the individual forecasts.

14 CFR 1260.145 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Higher Education, Hospitals, and Other Non-Profit Organizations Procurement Standards § 1260.145 Cost and..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

2 CFR 215.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS (OMB CIRCULAR... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

10 CFR 600.145 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Requirements for Grants and Cooperative Agreements With Institutions of Higher Education, Hospitals, and Other... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

43 CFR 12.945 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Agreements With Institutions of Higher Education, Hospitals, and Other Non-Profit Organizations Post-Award... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

2 CFR 215.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS (OMB CIRCULAR... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

14 CFR 1260.145 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Higher Education, Hospitals, and Other Non-Profit Organizations Procurement Standards § 1260.145 Cost and..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

43 CFR 12.945 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Agreements With Institutions of Higher Education, Hospitals, and Other Non-Profit Organizations Post-Award... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

43 CFR 12.945 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Agreements With Institutions of Higher Education, Hospitals, and Other Non-Profit Organizations Post-Award... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

45 CFR 2543.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-10-01

... SERVICE GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

45 CFR 2543.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-10-01

... SERVICE GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

14 CFR 1260.145 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Higher Education, Hospitals, and Other Non-Profit Organizations Procurement Standards § 1260.145 Cost and..., including the comparison of price quotations submitted, market prices and similar indicia, together with...

10 CFR 600.145 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Requirements for Grants and Cooperative Agreements With Institutions of Higher Education, Hospitals, and Other... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

45 CFR 2543.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-10-01

... SERVICE GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

10 CFR 600.145 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Requirements for Grants and Cooperative Agreements With Institutions of Higher Education, Hospitals, and Other... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

43 CFR 12.945 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Agreements With Institutions of Higher Education, Hospitals, and Other Non-Profit Organizations Post-Award... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

2 CFR 215.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS (OMB CIRCULAR... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

45 CFR 2543.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICE GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT... procurement action. Price analysis may be accomplished in various ways, including the comparison of price...

Improvement of forecast skill for severe weather by merging radar-based extrapolation and storm-scale NWP corrected forecast

NASA Astrophysics Data System (ADS)

Wang, Gaili; Wong, Wai-Kin; Hong, Yang; Liu, Liping; Dong, Jili; Xue, Ming

2015-03-01

The primary objective of this study is to improve the performance of deterministic high resolution rainfall forecasts caused by severe storms by merging an extrapolation radar-based scheme with a storm-scale Numerical Weather Prediction (NWP) model. Effectiveness of Multi-scale Tracking and Forecasting Radar Echoes (MTaRE) model was compared with that of a storm-scale NWP model named Advanced Regional Prediction System (ARPS) for forecasting a violent tornado event that developed over parts of western and much of central Oklahoma on May 24, 2011. Then the bias corrections were performed to improve the forecast accuracy of ARPS forecasts. Finally, the corrected ARPS forecast and radar-based extrapolation were optimally merged by using a hyperbolic tangent weight scheme. The comparison of forecast skill between MTaRE and ARPS in high spatial resolution of 0.01° × 0.01° and high temporal resolution of 5 min showed that MTaRE outperformed ARPS in terms of index of agreement and mean absolute error (MAE). MTaRE had a better Critical Success Index (CSI) for less than 20-min lead times and was comparable to ARPS for 20- to 50-min lead times, while ARPS had a better CSI for more than 50-min lead times. Bias correction significantly improved ARPS forecasts in terms of MAE and index of agreement, although the CSI of corrected ARPS forecasts was similar to that of the uncorrected ARPS forecasts. Moreover, optimally merging results using hyperbolic tangent weight scheme further improved the forecast accuracy and became more stable.

29 CFR 95.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 1 2011-07-01 2011-07-01 false Cost and price analysis. 95.45 Section 95.45 Labor Office of the Secretary of Labor GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

29 CFR 95.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 1 2012-07-01 2012-07-01 false Cost and price analysis. 95.45 Section 95.45 Labor Office of the Secretary of Labor GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

29 CFR 95.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 1 2013-07-01 2013-07-01 false Cost and price analysis. 95.45 Section 95.45 Labor Office of the Secretary of Labor GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

29 CFR 95.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 1 2014-07-01 2013-07-01 true Cost and price analysis. 95.45 Section 95.45 Labor Office of the Secretary of Labor GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

Simulations of Tropospheric NO2 by the Global Modeling Initiative (GMI) Model Utilizing Assimilated and Forecast Meteorological Fields: Comparison to Ozone Monitoring Instrument (OMI) Measurements

NASA Technical Reports Server (NTRS)

Rodriquez, J. M.; Yoshida, Y.; Duncan, B. N.; Bucsela, E. J.; Gleason, J. F.; Allen, D.; Pickering, K. E.

2007-01-01

We present simulations of the tropospheric composition for the years 2004 and 2005, carried out by the GMI Combined Stratosphere-Troposphere (Combo) model, at a resolution of 2degx2.5deg. The model includes a new parameterization of lightning sources of NO(x) which is coupled to the cloud mass fluxes in the adopted meteorological fields. These simulations use two different sets of input meteorological fields: a)late-look assimilated fields from the Global Modeling and Assimilation Office (GMAO), GEOS-4 system and b) 12-hour forecast fields initialized with the assimilated data. Comparison of the forecast to the assimilated fields indicates that the forecast fields exhibit less vigorous convection, and yield tropical precipitation fields in better agreement with observations. Since these simulations include a complete representation of the stratosphere, they provide realistic stratosphere-tropospheric fluxes of O3 and NO(y). Furthermore, the stratospheric contribution to total columns of different troposheric species can be subtracted in a consistent fashion, and the lightning production of NO(y) will depend on the adopted meteorological field. We concentrate here on the simulated tropospheric columns of NO2, and compare them to observations by the OM1 instrument for the years 2004 and 2005. The comparison is used to address these questions: a) is there a significant difference in the agreement/disagreement between simulations for these two different meteorological fields, and if so, what causes these differences?; b) how do the simulations compare to OMI observations, and does this comparison indicate an improvement in simulations with the forecast fields? c) what are the implications of these simulations for our understanding of the NO2 emissions over continental polluted regions?

Three essays on price dynamics and causations among energy markets and macroeconomic information

NASA Astrophysics Data System (ADS)

Hong, Sung Wook

This dissertation examines three important issues in energy markets: price dynamics, information flow, and structural change. We discuss each issue in detail, building empirical time series models, analyzing the results, and interpreting the findings. First, we examine the contemporaneous interdependencies and information flows among crude oil, natural gas, and electricity prices in the United States (US) through the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model, Directed Acyclic Graph (DAG) for contemporaneous causal structures and Bernanke factorization for price dynamic processes. Test results show that the DAG from residuals of out-of-sample-forecast is consistent with the DAG from residuals of within-sample-fit. The result supports innovation accounting analysis based on DAGs using residuals of out-of-sample-forecast. Second, we look at the effects of the federal fund rate and/or WTI crude oil price shock on US macroeconomic and financial indicators by using a Factor Augmented Vector Autoregression (FAVAR) model and a graphical model without any deductive assumption. The results show that, in contemporaneous time, the federal fund rate shock is exogenous as the identifying assumption in the Vector Autoregression (VAR) framework of the monetary shock transmission mechanism, whereas the WTI crude oil price return is not exogenous. Third, we examine price dynamics and contemporaneous causality among the price returns of WTI crude oil, gasoline, corn, and the S&P 500. We look for structural break points and then build an econometric model to find the consistent sub-periods having stable parameters in a given VAR framework and to explain recent movements and interdependency among returns. We found strong evidence of two structural breaks and contemporaneous causal relationships among the residuals, but also significant differences between contemporaneous causal structures for each sub-period.

Short-term forecasts gain in accuracy. [Regression technique using ''Box-Jenkins'' analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

Box-Jenkins time-series models offer accuracy for short-term forecasts that compare with large-scale macroeconomic forecasts. Utilities need to be able to forecast peak demand in order to plan their generating, transmitting, and distribution systems. This new method differs from conventional models by not assuming specific data patterns, but by fitting available data into a tentative pattern on the basis of auto-correlations. Three types of models (autoregressive, moving average, or mixed autoregressive/moving average) can be used according to which provides the most appropriate combination of autocorrelations and related derivatives. Major steps in choosing a model are identifying potential models, estimating the parametersmore » of the problem, and running a diagnostic check to see if the model fits the parameters. The Box-Jenkins technique is well suited for seasonal patterns, which makes it possible to have as short as hourly forecasts of load demand. With accuracy up to two years, the method will allow electricity price-elasticity forecasting that can be applied to facility planning and rate design. (DCK)« less

A channel dynamics model for real-time flood forecasting

USGS Publications Warehouse

Hoos, Anne B.; Koussis, Antonis D.; Beale, Guy O.

1989-01-01

A new channel dynamics scheme (alternative system predictor in real time (ASPIRE)), designed specifically for real-time river flow forecasting, is introduced to reduce uncertainty in the forecast. ASPIRE is a storage routing model that limits the influence of catchment model forecast errors to the downstream station closest to the catchment. Comparisons with the Muskingum routing scheme in field tests suggest that the ASPIRE scheme can provide more accurate forecasts, probably because discharge observations are used to a maximum advantage and routing reaches (and model errors in each reach) are uncoupled. Using ASPIRE in conjunction with the Kalman filter did not improve forecast accuracy relative to a deterministic updating procedure. Theoretical analysis suggests that this is due to a large process noise to measurement noise ratio.

Improvements in approaches to forecasting and evaluation techniques

NASA Astrophysics Data System (ADS)

Weatherhead, Elizabeth

2014-05-01

The US is embarking on an experiment to make significant and sustained improvements in weather forecasting. The effort stems from a series of community conversations that recognized the rapid advancements in observations, modeling and computing techniques in the academic, governmental and private sectors. The new directions and initial efforts will be summarized, including information on possibilities for international collaboration. Most new projects are scheduled to start in the last half of 2014. Several advancements include ensemble forecasting with global models, and new sharing of computing resources. Newly developed techniques for evaluating weather forecast models will be presented in detail. The approaches use statistical techniques that incorporate pair-wise comparisons of forecasts with observations and account for daily auto-correlation to assess appropriate uncertainty in forecast changes. Some of the new projects allow for international collaboration, particularly on the research components of the projects.

Deep-water oilfield development cost analysis and forecasting —— Take gulf of mexico for example

NASA Astrophysics Data System (ADS)

Shi, Mingyu; Wang, Jianjun; Yi, Chenggao; Bai, Jianhui; Wang, Jing

2017-11-01

Gulf of Mexico (GoM) is the earliest offshore oilfield which has ever been developed. It tends to breed increasingly value of efficient, secure and cheap key technology of deep-water development. Thus, the analyze of development expenditure in this area is significantly important the evaluation concept of deep-water oilfield all over the world. This article emphasizes on deep-water development concept and EPC contract value in GoM in recent 10 years in case of comparison and selection to the economic efficiency. Besides, the QUETOR has been put into use in this research processes the largest upstream cost database to simulate and calculate the calculating examples’ expenditure. By analyzing and forecasting the deep-water oilfield development expenditure, this article explores the relevance between expenditure index and oil price.

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

NASA Astrophysics Data System (ADS)

Rogelis, María Carolina; Werner, Micha

2018-02-01

Numerical weather prediction (NWP) models are fundamental to extend forecast lead times beyond the concentration time of a watershed. Particularly for flash flood forecasting in tropical mountainous watersheds, forecast precipitation is required to provide timely warnings. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that bias correction can provide, in a tropical mountainous area. The paper focuses on the comparison of streamflows obtained from the post-processed precipitation forecasts, particularly the comparison of ensemble forecasts and their potential in providing skilful flood forecasts. The Weather Research and Forecasting (WRF) model is used to produce precipitation forecasts that are post-processed and used to drive a hydrologic model. Discharge forecasts obtained from the hydrological model are used to assess the skill of the WRF model. The results show that post-processed WRF precipitation adds value to the flood early warning system when compared to zero-precipitation forecasts, although the precipitation forecast used in this analysis showed little added value when compared to climatology. However, the reduction of biases obtained from the post-processed ensembles show the potential of this method and model to provide usable precipitation forecasts in tropical mountainous watersheds. The need for more detailed evaluation of the WRF model in the study area is highlighted, particularly the identification of the most suitable parameterisation, due to the inability of the model to adequately represent the convective precipitation found in the study area.

Air Quality Forecasts Using the NASA GEOS Model

NASA Technical Reports Server (NTRS)

Keller, Christoph A.; Knowland, K. Emma; Nielsen, Jon E.; Orbe, Clara; Ott, Lesley; Pawson, Steven; Saunders, Emily; Duncan, Bryan; Follette-Cook, Melanie; Liu, Junhua;

Spatial Pattern Classification for More Accurate Forecasting of Variable Energy Resources

NASA Astrophysics Data System (ADS)

Novakovskaia, E.; Hayes, C.; Collier, C.

2014-12-01

The accuracy of solar and wind forecasts is becoming increasingly essential as grid operators continue to integrate additional renewable generation onto the electric grid. Forecast errors affect rate payers, grid operators, wind and solar plant maintenance crews and energy traders through increases in prices, project down time or lost revenue. While extensive and beneficial efforts were undertaken in recent years to improve physical weather models for a broad spectrum of applications these improvements have generally not been sufficient to meet the accuracy demands of system planners. For renewables, these models are often used in conjunction with additional statistical models utilizing both meteorological observations and the power generation data. Forecast accuracy can be dependent on specific weather regimes for a given location. To account for these dependencies it is important that parameterizations used in statistical models change as the regime changes. An automated tool, based on an artificial neural network model, has been developed to identify different weather regimes as they impact power output forecast accuracy at wind or solar farms. In this study, improvements in forecast accuracy were analyzed for varying time horizons for wind farms and utility-scale PV plants located in different geographical regions.

A petroleum discovery-rate forecast revisited-The problem of field growth

USGS Publications Warehouse

Drew, L.J.; Schuenemeyer, J.H.

1992-01-01

A forecast of the future rates of discovery of crude oil and natural gas for the 123,027-km2 Miocene/Pliocene trend in the Gulf of Mexico was made in 1980. This forecast was evaluated in 1988 by comparing two sets of data: (1) the actual versus the forecasted number of fields discovered, and (2) the actual versus the forecasted volumes of crude oil and natural gas discovered with the drilling of 1,820 wildcat wells along the trend between January 1, 1977, and December 31, 1985. The forecast specified that this level of drilling would result in the discovery of 217 fields containing 1.78 billion barrels of oil equivalent; however, 238 fields containing 3.57 billion barrels of oil equivalent were actually discovered. This underestimation is attributed to biases introduced by field growth and, to a lesser degree, the artificially low, pre-1970's price of natural gas that prevented many smaller gas fields from being brought into production at the time of their discovery; most of these fields contained less than 50 billion cubic feet of producible natural gas. ?? 1992 Oxford University Press.

A comparison of observed and forecast energetics over North America

NASA Technical Reports Server (NTRS)

Baker, W. E.; Brin, Y.

1985-01-01

The observed kinetic energy balance is calculated over North America and compared with that computed from forecast fields for the 13-15 January 1979 cyclone. The FGGE upper-air rawinsonde network serves as the observational database while the forecast energetics are derived from a numerical integration with the GLAS fourth-order general circulation model initialized at 00 GMT 13 January. Maps of the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. Both the forecast and observations exhibit the lower and upper tropospheric maxima in vertical profiles of kinetic energy generation and dissipation typically found in cyclonic disturbances. An interesting time lag is noted in the observational analysis with the maximum observed kinetic energy occurring 12 h later than the maximum eddy conversion over the same region.

Relationship between the Uncompensated Price Elasticity and the Income Elasticity of Demand under Conditions of Additive Preferences.

PubMed

Sabatelli, Lorenzo

2016-01-01

Income and price elasticity of demand quantify the responsiveness of markets to changes in income and in prices, respectively. Under the assumptions of utility maximization and preference independence (additive preferences), mathematical relationships between income elasticity values and the uncompensated own and cross price elasticity of demand are here derived using the differential approach to demand analysis. Key parameters are: the elasticity of the marginal utility of income, and the average budget share. The proposed method can be used to forecast the direct and indirect impact of price changes and of financial instruments of policy using available estimates of the income elasticity of demand.

36 CFR § 1210.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-07-01

... HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award Requirements Procurement... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

Forecasting volatility of SSEC in Chinese stock market using multifractal analysis

NASA Astrophysics Data System (ADS)

Wei, Yu; Wang, Peng

2008-03-01

In this paper, taking about 7 years’ high-frequency data of the Shanghai Stock Exchange Composite Index (SSEC) as an example, we propose a daily volatility measure based on the multifractal spectrum of the high-frequency price variability within a trading day. An ARFIMA model is used to depict the dynamics of this multifractal volatility (MFV) measures. The one-day ahead volatility forecasting performances of the MFV model and some other existing volatility models, such as the realized volatility model, stochastic volatility model and GARCH, are evaluated by the superior prediction ability (SPA) test. The empirical results show that under several loss functions, the MFV model obtains the best forecasting accuracy.

Some Evidence on the Importance of Sticky Prices.

ERIC Educational Resources Information Center

Bils, Mark; Klenow, Peter J.

2004-01-01

We examine the frequency of price changes for 350 categories of goods and services covering about 70 percent of consumer spending, on the basis of unpublished data from the Bureau of Labor Statistics for 1995-97. In comparison with previous studies, we find much more frequent price changes, with haft of prices lasting less than 4.3 months. Even…

14 CFR § 1260.145 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Institutions of Higher Education, Hospitals, and Other Non-Profit Organizations Procurement Standards § 1260... ways, including the comparison of price quotations submitted, market prices and similar indicia...

On the importance of commodity and energy price shocks for the macroeconomy

NASA Astrophysics Data System (ADS)

Edelstein, Paul S.

Although higher commodity prices are commonly thought to presage higher rates of inflation, the existing literature suggests that the predictive power of commodity prices for inflation has waned since the 1980s. In the first chapter, I show that this result can be overturned using state-of-the-art forecast combination methods. Moreover, commodity prices are shown to contain predictive information not contained in the leading principal components of a broad set of macroeconomic and financial variables. These improved inflation forecasts are of little value, however, for predicting actual Fed policy decisions. The remaining two chapters study the effect of energy price shocks on U.S. consumer and business expenditures. In the second chapter, I show that there is no statistical support for the presence of asymmetries in the response of real consumption to energy price increases and decreases. This finding has important implications for empirical and theoretical models of the transmission of energy price shocks. I then quantify the direct effect on real consumption of (1) unanticipated changes in discretionary income, (2) shifts in precautionary savings, and (3) changes in the operating cost of energy-using durables. Finally, I trace the declining importance of energy price shocks relative to the 1970s to changes in the composition of U.S. automobile production and the declining overall importance of the U.S. automobile sector. An alternative source of asymmetry is the response of nonresidential fixed investment to energy price shocks. In the third chapter, I show that the apparent asymmetry in the estimated responses of business fixed investment in equipment and structures is largely an artifact (1) of the aggregation of mining-related expenditures by the oil, natural gas, and coal mining industry and all other expenditures, and (2) of ignoring an exogenous shift in investment caused by the 1986 Tax Reform Act. Once symmetry is imposed and miningrelated expenditures

Comparison of kinetic and air temperatures in Budapest aiming applications in weather forecasting

NASA Astrophysics Data System (ADS)

Mika, Janos; Nemeth, Akos; Bela Olah, Andras; Dezso, Zsuzsanna

2010-05-01

Moderate Resolution Imaging Spectroradiometer (MODIS) based kinetic temperature data are compared with the surface air temperature data at the four weather stations in Budapest, Hun-gary. Dependence of these temperature characteristics on weather conditions, characterised by macrosynoptic types and by objective weather types, is in the focus of the study. Day- and night-time kinetic temperature series are used from the period 2001-2008. Four automatic stations are also used as the surface-based control variables. The four MODIS-pixels, covering one station, each, are the sites of our comparison. One of the four stations has strictly urban situation at the roof level in a strongly built-in region of Budapest. Another one, used as background rural station is at the east-west edge of the town with gar-dened environment. Two other stations are positioned near the river Danube at the northern and southern edges of Budapest, still under mezo-scale effect of the city. The number of elaborated hourly values is 4300-4400 above each pixel, depending on the cloudiness. At the four station automatic observations on air temperature, cloudiness (=0), relative humidity and wind-speed are observed in the hours of the MODIS observations. From these elements air temperature is used for comparison with the satellite-based kinetic temperature, and also as the main components of the Physiologically Equivalent Temperature (PET), de-rived to characterise usefulness of the kinetic temperature. Our first aim is to specify detailed relationship between the two temperatures consider-ing the seasonal and diurnal cycles and synoptic situation. This comparison is also performed by using the PET to establish which kind of temperature reminds this human bioclimatic in-dex better. If we could establish effective relationships with the synoptic situations (or weather types) we could use them in two further applications. The first one is the everyday forecasting of dangerous situations within the

41 CFR 105-72.505 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-07-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS 72.50-Post-Award Requirements/Procurement Standards... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

41 CFR 105-72.505 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS 72.50-Post-Award Requirements/Procurement Standards... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

41 CFR 105-72.505 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-01-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS 72.50-Post-Award Requirements/Procurement Standards... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

41 CFR 105-72.505 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS 72.50-Post-Award Requirements/Procurement Standards... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

Teaching ocean wave forecasting using computer-generated visualization and animation—Part 1: sea forecasting

NASA Astrophysics Data System (ADS)

Whitford, Dennis J.

2002-05-01

Ocean waves are the most recognized phenomena in oceanography. Unfortunately, undergraduate study of ocean wave dynamics and forecasting involves mathematics and physics and therefore can pose difficulties with some students because of the subject's interrelated dependence on time and space. Verbal descriptions and two-dimensional illustrations are often insufficient for student comprehension. Computer-generated visualization and animation offer a visually intuitive and pedagogically sound medium to present geoscience, yet there are very few oceanographic examples. A two-part article series is offered to explain ocean wave forecasting using computer-generated visualization and animation. This paper, Part 1, addresses forecasting of sea wave conditions and serves as the basis for the more difficult topic of swell wave forecasting addressed in Part 2. Computer-aided visualization and animation, accompanied by oral explanation, are a welcome pedagogical supplement to more traditional methods of instruction. In this article, several MATLAB ® software programs have been written to visualize and animate development and comparison of wave spectra, wave interference, and forecasting of sea conditions. These programs also set the stage for the more advanced and difficult animation topics in Part 2. The programs are user-friendly, interactive, easy to modify, and developed as instructional tools. By using these software programs, teachers can enhance their instruction of these topics with colorful visualizations and animation without requiring an extensive background in computer programming.

Lead and the London Metal Exchange — a happy marriage? The outlook for prices and pricing issues confronting the lead industry

NASA Astrophysics Data System (ADS)

Keen, A.

The outlook for the supply-demand balance for refined lead is addressed and takes into account the growing non-fundamental forces on price determination. The market for refined lead is presently experiencing its first year of surplus since the major crisis of the early 1990s. Earlier in the decade, the dissolution of the Soviet Union and recession in developed economies led to a significant rise in London Metal Exchange (LME) stocks. An acceleration absorbed these stocks in an 18-month period in the mid-1990s, and LME lead prices reacted to the market deficit by peaking above US900. Since then the market has balanced, yet prices have declined steadily to less that 50% of their peak levels. It is argued that, on fundamental grounds, prices have fallen below justified levels. As much of the reason for this depression between 1997 and 1999 has been the generally depressive effect of the Asian economic crisis on financial markets, the level of lead prices may now be due for a correction. Other metals have begun to increase during the first half of 1999 and lead, given its neutral fundamental outlook, is now poised to participate in the generally more buoyant moods across LME metals. An increase of approximately 10% in average LME 3-month settlement prices is forecast and will result in annual average prices of US 570/tonne over the course of 1999. Monthly averages and spot prices are predicted to exceed this level, particularly during peak third-quarter demand.

Economic benefits of improved meteorological forecasts - The construction industry

NASA Technical Reports Server (NTRS)

Bhattacharyya, R. K.; Greenberg, J. S.

1976-01-01

Estimates are made of the potential economic benefits accruing to particular industries from timely utilization of satellite-derived six-hour weather forecasts, and of economic penalties resulting from failure to utilize such forecasts in day-to-day planning. The cost estimate study is centered on the U.S. construction industry, with results simplified to yes/no 6-hr forecasts on thunderstorm activity and work/no work decisions. Effects of weather elements (thunderstorms, snow and sleet) on various construction operations are indicated. Potential dollar benefits for other industries, including air transportation and other forms of transportation, are diagrammed for comparison. Geosynchronous satellites such as STORMSAT, SEOS, and SMS/GOES are considered as sources of the forecast data.

A stochastic delay model for pricing debt and equity: Numerical techniques and applications

NASA Astrophysics Data System (ADS)

Tambue, Antoine; Kemajou Brown, Elisabeth; Mohammed, Salah

2015-01-01

Delayed nonlinear models for pricing corporate liabilities and European options were recently developed. Using self-financed strategy and duplication we were able to derive a Random Partial Differential Equation (RPDE) whose solutions describe the evolution of debt and equity values of a corporate in the last delay period interval in the accompanied paper (Kemajou et al., 2012) [14]. In this paper, we provide robust numerical techniques to solve the delayed nonlinear model for the corporate value, along with the corresponding RPDEs modeling the debt and equity values of the corporate. Using financial data from some firms, we forecast and compare numerical solutions from both the nonlinear delayed model and classical Merton model with the real corporate data. From this comparison, it comes up that in corporate finance the past dependence of the firm value process may be an important feature and therefore should not be ignored.

16 CFR 233.2 - Retail price comparisons; comparable value comparisons.

Code of Federal Regulations, 2010 CFR

2010-01-01

... which substantial sales of the article are being made in the area—that is, a sufficient number of sales... technique. Retailer Doe advertises Brand X pens as having a “Retail Value $15.00, My Price $7.50,” when the...

On the dynamics of the world demographic transition and financial-economic crises forecasts

NASA Astrophysics Data System (ADS)

Akaev, A.; Sadovnichy, V.; Korotayev, A.

2012-05-01

The article considers dynamic processes involving non-linear power-law behavior in such apparently diverse spheres, as demographic dynamics and dynamics of prices of highly liquid commodities such as oil and gold. All the respective variables exhibit features of explosive growth containing precursors indicating approaching phase transitions/catastrophes/crises. The first part of the article analyzes mathematical models of demographic dynamics that describe various scenarios of demographic development in the post-phase-transition period, including a model that takes the limitedness of the Earth carrying capacity into account. This model points to a critical point in the early 2050s, when the world population, after reaching its maximum value may decrease afterward stabilizing then at a certain stationary level. The article presents an analysis of the influence of the demographic transition (directly connected with the hyperexponential growth of the world population) on the global socioeconomic and geopolitical development. The second part deals with the phenomenon of explosive growth of prices of such highly liquid commodities as oil and gold. It is demonstrated that at present the respective processes could be regarded as precursors of waves of the global financial-economic crisis that will demand the change of the current global economic and political system. It is also shown that the moments of the start of the first and second waves of the current global crisis could have been forecasted with a model of accelerating log-periodic fluctuations superimposed over a power-law trend with a finite singularity developed by Didier Sornette and collaborators. With respect to the oil prices, it is shown that it was possible to forecast the 2008 crisis with a precision up to a month already in 2007. The gold price dynamics was used to calculate the possible time of the start of the second wave of the global crisis (July-August 2011); note that this forecast has turned out

NOAA's weather forecasts go hyper-local with next-generation weather

Science.gov Websites

model NOAA HOME WEATHER OCEANS FISHERIES CHARTING SATELLITES CLIMATE RESEARCH COASTS CAREERS with next-generation weather model New model will help forecasters predict a storm's path, timing and intensity better than ever September 30, 2014 This is a comparison of two weather forecast models looking

Assessment of Forecast Sensitivity to Observation and Its Application to Satellite Radiances

NASA Astrophysics Data System (ADS)

Ide, K.

2017-12-01

The Forecast sensitivity to observation provides practical and useful metric for the assessment of observation impact without conducting computationally intensive data denial experiments. Quite often complex data assimilation systems use a simplified version of the forecast sensitivity formulation based on ensembles. In this talk, we first present the comparison of forecast sensitivity for 4DVar, Hybrid-4DEnVar, and 4DEnKF with or without such simplifications using a highly nonlinear model. We then present the results of ensemble forecast sensitivity to satellite radiance observations for Hybrid-4DEnVart using NOAA's Global Forecast System.

Relationship between the Uncompensated Price Elasticity and the Income Elasticity of Demand under Conditions of Additive Preferences

PubMed Central

Sabatelli, Lorenzo

2016-01-01

Income and price elasticity of demand quantify the responsiveness of markets to changes in income and in prices, respectively. Under the assumptions of utility maximization and preference independence (additive preferences), mathematical relationships between income elasticity values and the uncompensated own and cross price elasticity of demand are here derived using the differential approach to demand analysis. Key parameters are: the elasticity of the marginal utility of income, and the average budget share. The proposed method can be used to forecast the direct and indirect impact of price changes and of financial instruments of policy using available estimates of the income elasticity of demand. PMID:26999511

Statistical Earthquake Focal Mechanism Forecasts

NASA Astrophysics Data System (ADS)

Kagan, Y. Y.; Jackson, D. D.

2013-12-01

The new whole Earth focal mechanism forecast, based on the GCMT catalog, has been created. In the present forecast, the sum of normalized seismic moment tensors within 1000 km radius is calculated and the P- and T-axes for the focal mechanism are evaluated on the basis of the sum. Simultaneously we calculate an average rotation angle between the forecasted mechanism and all the surrounding mechanisms. This average angle shows tectonic complexity of a region and indicates the accuracy of the prediction. The method was originally proposed by Kagan and Jackson (1994, JGR). Recent interest by CSEP and GEM has motivated some improvements, particularly to extend the previous forecast to polar and near-polar regions. The major problem in extending the forecast is the focal mechanism calculation on a spherical surface. In the previous forecast as our average focal mechanism was computed, it was assumed that longitude lines are approximately parallel within 1000 km radius. This is largely accurate in the equatorial and near-equatorial areas. However, when one approaches the 75 degree latitude, the longitude lines are no longer parallel: the bearing (azimuthal) difference at points separated by 1000 km reach about 35 degrees. In most situations a forecast point where we calculate an average focal mechanism is surrounded by earthquakes, so a bias should not be strong due to the difference effect cancellation. But if we move into polar regions, the bearing difference could approach 180 degrees. In a modified program focal mechanisms have been projected on a plane tangent to a sphere at a forecast point. New longitude axes which are parallel in the tangent plane are corrected for the bearing difference. A comparison with the old 75S-75N forecast shows that in equatorial regions the forecasted focal mechanisms are almost the same, and the difference in the forecasted focal mechanisms rotation angle is close to zero. However, though the forecasted focal mechanisms are similar

A Comparison of Some Difference Schemes for a Parabolic Problem of Zero-Coupon Bond Pricing

NASA Astrophysics Data System (ADS)

Chernogorova, Tatiana; Vulkov, Lubin

2009-11-01

This paper describes a comparison of some numerical methods for solving a convection-diffusion equation subjected by dynamical boundary conditions which arises in the zero-coupon bond pricing. The one-dimensional convection-diffusion equation is solved by using difference schemes with weights including standard difference schemes as the monotone Samarskii's scheme, FTCS and Crank-Nicolson methods. The schemes are free of spurious oscillations and satisfy the positivity and maximum principle as demanded for the financial and diffusive solution. Numerical results are compared with analytical solutions.

7 CFR 3019.45 - Cost and price analysis.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Agriculture Regulations of the Department of Agriculture (Continued) OFFICE OF THE CHIEF FINANCIAL OFFICER, DEPARTMENT OF AGRICULTURE UNIFORM ADMINISTRATIVE REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF... accomplished in various ways, including the comparison of price quotations submitted, market prices and similar...

Models for forecasting energy use in the US farm sector

NASA Astrophysics Data System (ADS)

Christensen, L. R.

1981-07-01

Econometric models were developed and estimated for the purpose of forecasting electricity and petroleum demand in US agriculture. A structural approach is pursued which takes account of the fact that the quantity demanded of any one input is a decision made in conjunction with other input decisions. Three different functional forms of varying degrees of complexity are specified for the structural cost function, which describes the cost of production as a function of the level of output and factor prices. Demand for materials (all purchased inputs) is derived from these models. A separate model which break this demand up into demand for the four components of materials is used to produce forecasts of electricity and petroleum is a stepwise manner.

Comparative analysis of used car price evaluation models

NASA Astrophysics Data System (ADS)

Chen, Chuancan; Hao, Lulu; Xu, Cong

2017-05-01

An accurate used car price evaluation is a catalyst for the healthy development of used car market. Data mining has been applied to predict used car price in several articles. However, little is studied on the comparison of using different algorithms in used car price estimation. This paper collects more than 100,000 used car dealing records throughout China to do empirical analysis on a thorough comparison of two algorithms: linear regression and random forest. These two algorithms are used to predict used car price in three different models: model for a certain car make, model for a certain car series and universal model. Results show that random forest has a stable but not ideal effect in price evaluation model for a certain car make, but it shows great advantage in the universal model compared with linear regression. This indicates that random forest is an optimal algorithm when handling complex models with a large number of variables and samples, yet it shows no obvious advantage when coping with simple models with less variables.

Regional Comparisons, Spatial Aggregation, and Asymmetry of Price Pass-Through

EIA Publications

2005-01-01

Spot to retail price pass-through behavior of the U.S. gasoline market was investigated at the national and regional levels, using weekly wholesale and retail motor gasoline prices from January 2000 to the present.

A quality assessment of the MARS crop yield forecasting system for the European Union

NASA Astrophysics Data System (ADS)

van der Velde, Marijn; Bareuth, Bettina

2015-04-01

Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

Surface wave effect on the upper ocean in marine forecast

NASA Astrophysics Data System (ADS)

Wang, Guansuo; Qiao, Fangli; Xia, Changshui; Zhao, Chang

2015-04-01

An Operational Coupled Forecast System for the seas off China and adjacent (OCFS-C) is constructed based on the paralleled wave-circulation coupled model, which is tested with comprehensive experiments and operational since November 1st, 2007. The main feature of the system is that the wave-induced mixing is considered in circulation model. Daily analyses and three day forecasts of three-dimensional temperature, salinity, currents and wave height are produced. Coverage is global at 1/2 degreed resolution with nested models up to 1/24 degree resolution in China Sea. Daily remote sensing sea surface temperatures (SST) are taken to relax to an analytical product as hot restarting fields for OCFS-C by the Nudging techniques. Forecasting-data inter-comparisons are performed to measure the effectiveness of OCFS-C in predicting upper-ocean quantities including SST, mixed layer depth (MLD) and subsurface temperature. The variety of performance with lead time and real-time is discussed as well using the daily statistic results for SST between forecast and satellite data. Several buoy observations and many Argo profiles are used for this validation. Except the conventional statistical metrics, non-dimension skill scores (SS) is taken to estimate forecast skill. Model SST comparisons with more one year-long SST time series from 2 buoys given a large SS value (more than 0.90). And skill in predicting the seasonal variability of SST is confirmed. Model subsurface temperature comparisons with that from a lot of Argo profiles indicated that OCFS-C has low skill in predicting subsurface temperatures between 80m and 120m. Inter-comparisons of MLD reveal that MLD from model is shallower than that from Argo profiles by about 12m. QCFS-C is successful and steady in predicting MLD. The daily statistic results for SST between 1-d, 2-d and 3-d forecast and data is adopted to describe variability of Skill in predicting SST with lead time or real time. In a word QCFS-C shows reasonable

Calls Forecast for the Moscow Ambulance Service. The Impact of Weather Forecast

NASA Astrophysics Data System (ADS)

Gordin, Vladimir; Bykov, Philipp

2015-04-01

We use the known statistics of the calls for the current and previous days to predict them for tomorrow and for the following days. We assume that this algorithm will work operatively, will cyclically update the available information and will move the horizon of the forecast. Sure, the accuracy of such forecasts depends on their lead time, and from a choice of some group of diagnoses. For comparison we used the error of the inertial forecast (tomorrow there will be the same number of calls as today). Our technology has demonstrated accuracy that is approximately two times better compared to the inertial forecast. We obtained the following result: the number of calls depends on the actual weather in the city as well as on its rate of change. We were interested in the accuracy of the forecast for 12-hour sum of the calls in real situations. We evaluate the impact of the meteorological errors [1] on the forecast errors of the number of Ambulance calls. The weather and the Ambulance calls number both have seasonal tendencies. Therefore, if we have medical information from one city only, we should separate the impacts of such predictors as "annual variations in the number of calls" and "weather". We need to consider the seasonal tendencies (associated, e. g. with the seasonal migration of the population) and the impact of the air temperature simultaneously, rather than sequentially. We forecasted separately the number of calls with diagnoses of cardiovascular group, where it was demonstrated the advantage of the forecasting method, when we use the maximum daily air temperature as a predictor. We have a chance to evaluate statistically the influence of meteorological factors on the dynamics of medical problems. In some cases it may be useful for understanding of the physiology of disease and possible treatment options. We can assimilate some personal archives of medical parameters for the individuals with concrete diseases and the relative meteorological archive. As a

Global strategies to reduce the price of antiretroviral medicines: evidence from transactional databases.

PubMed

Waning, Brenda; Kaplan, Warren; King, Alexis C; Lawrence, Danielle A; Leufkens, Hubert G; Fox, Matthew P

2009-07-01

To estimate the impact of global strategies, such as pooled procurement arrangements, third-party price negotiation and differential pricing, on reducing the price of antiretrovirals (ARVs), which currently hinders universal access to HIV/AIDS treatment. We estimated the impact of global strategies to reduce ARV prices using data on 7253 procurement transactions (July 2002-October 2007) from databases hosted by WHO and the Global Fund to Fight AIDS, Tuberculosis and Malaria. For 19 of 24 ARV dosage forms, we detected no association between price and volume purchased. For the other five ARVs, high-volume purchases were 4-21% less expensive than medium- or low-volume purchases. Nine of 13 generic ARVs were priced 6-36% lower when purchased under the Clinton Foundation HIV/AIDS Initiative (CHAI). Fifteen of 18 branded ARVs were priced 23-498% higher for differentially priced purchases compared with non-CHAI generic purchases. However, two branded, differentially priced ARVs were priced 63% and 73% lower, respectively, than generic non-CHAI equivalents. Large purchase volumes did not necessarily result in lower ARV prices. Although current plans for pooled procurement will further increase purchase volumes, savings are uncertain and should be balanced against programmatic costs. Third-party negotiation by CHAI resulted in lower generic ARV prices. Generics were less expensive than differentially priced branded ARVs, except where little generic competition exists. Alternative strategies for reducing ARV prices, such as streamlining financial management systems, improving demand forecasting and removing barriers to generics, should be explored.

Investigating market efficiency through a forecasting model based on differential equations

NASA Astrophysics Data System (ADS)

de Resende, Charlene C.; Pereira, Adriano C. M.; Cardoso, Rodrigo T. N.; de Magalhães, A. R. Bosco

2017-05-01

A new differential equation based model for stock price trend forecast is proposed as a tool to investigate efficiency in an emerging market. Its predictive power showed statistically to be higher than the one of a completely random model, signaling towards the presence of arbitrage opportunities. Conditions for accuracy to be enhanced are investigated, and application of the model as part of a trading strategy is discussed.

Determining and Forecasting Savings from Competing Previously Sole Source/Noncompetitive Contracts

DTIC Science & Technology

1978-10-01

SUMMARY A. BACKGROUND. Within the defense market , It is difficult to isolate, identify and quantify the impact of competition on acquisition costs...63 C. F04iCASTING METhODOLOGY .................. . 7 0. COMPETITION INDEX . . . . . . . . . . . . . . . . . . .. . 77 E . USE AS A FORECASTING TOOL...program is still active. e . From this projection, calculate the actual total contract price coiencing with the buy-out competition by multiplying the

State prescription drug price Web sites: how useful to consumers?

PubMed

Tu, Ha T; Corey, Catherine G

2008-02-01

To aid consumers in comparing prescription drug costs, many states have launched Web sites to publish drug prices offered by local retail pharmacies. The current push to make retail pharmacy prices accessible to consumers is part of a much broader movement to increase price transparency throughout the health-care sector. Efforts to encourage price-based shopping for hospital and physician services have encountered widespread concerns, both on grounds that prices for complex services are difficult to measure and compare accurately and that quality varies substantially across providers. Experts agree, however, that prescription drugs are much easier to shop for than other, more complex health services. However, extensive gaps in available price information--the result of relying on Medicaid data--seriously hamper the effectiveness of state drug price-comparison Web sites, according to a new study by the Center for Studying Health System Change (HSC). An alternative approach--requiring pharmacies to submit price lists to the states--would improve the usefulness of price information, but pharmacies typically oppose such a mandate. Another limitation of most state Web sites is that price information is restricted to local pharmacies, when online pharmacies, both U.S. and foreign, often sell prescription drugs at substantially lower prices. To further enhance consumer shopping tools, states might consider expanding the types of information provided, including online pharmacy comparison tools, lists of deeply discounted generic drugs offered by discount retailers, and lists of local pharmacies offering price matches.

Tourism demand in the Algarve region: Evolution and forecast using SVARMA models

NASA Astrophysics Data System (ADS)

Lopes, Isabel Cristina; Soares, Filomena; Silva, Eliana Costa e.

2017-06-01

Tourism is one of the Portuguese economy's key sectors, and its relative weight has grown over recent years. The Algarve region is particularly focused on attracting foreign tourists and has built over the years a large offer of diversified hotel units. In this paper we present multivariate time series approach to forecast the number of overnight stays in hotel units (hotels, guesthouses or hostels, and tourist apartments) in Algarve. We adjust a seasonal vector autoregressive and moving averages model (SVARMA) to monthly data between 2006 and 2016. The forecast values were compared with the actual values of the overnight stays in Algarve in 2016 and led to a MAPE of 15.1% and RMSE= 53847.28. The MAPE for the Hotel series was merely 4.56%. These forecast values can be used by a hotel manager to predict their occupancy and to determine the best pricing policy.

An application of ensemble/multi model approach for wind power production forecasting

NASA Astrophysics Data System (ADS)

Alessandrini, S.; Pinson, P.; Hagedorn, R.; Decimi, G.; Sperati, S.

2011-02-01

The wind power forecasts of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast applied in this study is based on meteorological models that provide the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. For this purpose a training of a Neural Network (NN) to link directly the forecasted meteorological data and the power data has been performed. One wind farm has been examined located in a mountain area in the south of Italy (Sicily). First we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by the combination of models (RAMS, ECMWF deterministic, LAMI). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error (normalized by nominal power) of at least 1% compared to the singles models approach. Finally we have focused on the possibility of using the ensemble model system (EPS by ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first three days ahead period.

A Bayesian Assessment of Seismic Semi-Periodicity Forecasts

NASA Astrophysics Data System (ADS)

Nava, F.; Quinteros, C.; Glowacka, E.; Frez, J.

2016-01-01

Among the schemes for earthquake forecasting, the search for semi-periodicity during large earthquakes in a given seismogenic region plays an important role. When considering earthquake forecasts based on semi-periodic sequence identification, the Bayesian formalism is a useful tool for: (1) assessing how well a given earthquake satisfies a previously made forecast; (2) re-evaluating the semi-periodic sequence probability; and (3) testing other prior estimations of the sequence probability. A comparison of Bayesian estimates with updated estimates of semi-periodic sequences that incorporate new data not used in the original estimates shows extremely good agreement, indicating that: (1) the probability that a semi-periodic sequence is not due to chance is an appropriate estimate for the prior sequence probability estimate; and (2) the Bayesian formalism does a very good job of estimating corrected semi-periodicity probabilities, using slightly less data than that used for updated estimates. The Bayesian approach is exemplified explicitly by its application to the Parkfield semi-periodic forecast, and results are given for its application to other forecasts in Japan and Venezuela.

Evaluation of Air Force and Navy Demand Forecasting Systems

DTIC Science & Technology

1994-01-01

forecasting approach, the Air Force Material Command is questioning the adoption of the Navy’s Statistical Demand Forecasting System ( Gitman , 1994). The...Recoverable Item Process in the Requirements Data Bank System is to manage reparable spare parts ( Gitman , 1994). Although RDB will have the capability of...D062) ( Gitman , 1994). Since a comparison is made to address Air Force concerns, this research only limits its analysis to the range of Air Force

Review of alternative measures of softwood sawtimber prices in the United States

Treesearch

Henry Spelter

2005-01-01

This study compares prices from various timber market reports and an estimate of timber value derived from product-selling prices and manufacturing costs. In the South, two primary sources of timber price information are Forest2Market (F2M) and Timber Mart-South (TMS). Comparisons showed that F2M prices are generally higher than TMS prices for both stumpage and...

Comparison of Conventional and ANN Models for River Flow Forecasting

NASA Astrophysics Data System (ADS)

Jain, A.; Ganti, R.

2011-12-01

Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. River flow is generally estimated using time series or rainfall-runoff models. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been extensively adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conventional models. In this paper, a comparative study has been carried out for river flow forecasting using the conventional and ANN models. Among the conventional models, multiple linear, and non linear regression, and time series models of auto regressive (AR) type have been developed. Feed forward neural network model structure trained using the back propagation algorithm, a gradient search method, was adopted. The daily river flow data derived from Godavari Basin @ Polavaram, Andhra Pradesh, India have been employed to develop all the models included here. Two inputs, flows at two past time steps, (Q(t-1) and Q(t-2)) were selected using partial auto correlation analysis for forecasting flow at time t, Q(t). A wide range of error statistics have been used to evaluate the performance of all the models developed in this study. It has been found that the regression and AR models performed comparably, and the ANN model performed the best amongst all the models investigated in this study. It is concluded that ANN model should be adopted in real catchments for hydrological modeling and forecasting.

Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

NASA Astrophysics Data System (ADS)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

FAA Long-Range Aviation Forecasts Fiscal Years 2005-2020

DTIC Science & Technology

1993-09-01

assumptions translate into somewhat slower growth of aviation activity and FAA workload measures during the extended 16 -year period (2004 to 2020) than was...OPERATIONS 1.8 1.2 INSTRUMENT OPERATIONS 2.0 1.3 IFR AIRCRAFT HANDLED 2.0 1.3 FLIGHT SERVICE STTIONS (0.2) 0.1 2 II. LONG-RANGE FORECAST ASSUMPTIONS The...product (GDP), adjusted for price changes and expressed in 1987 dollars, will average 1.9 percent annually over the extended 16 -year fore- cast period

Comparison between GSTAR and GSTAR-Kalman Filter models on inflation rate forecasting in East Java

NASA Astrophysics Data System (ADS)

Rahma Prillantika, Jessica; Apriliani, Erna; Wahyuningsih, Nuri

2018-03-01

Up to now, we often find data which have correlation between time and location. This data also known as spatial data. Inflation rate is one type of spatial data because it is not only related to the events of the previous time, but also has relevance to the other location or elsewhere. In this research, we do comparison between GSTAR model and GSTAR-Kalman Filter to get prediction which have small error rate. Kalman Filter is one estimator that estimates state changes due to noise from white noise. The final result shows that Kalman Filter is able to improve the GSTAR forecast result. This is shown through simulation results in the form of graphs and clarified with smaller RMSE values.

Metric optimisation for analogue forecasting by simulated annealing

NASA Astrophysics Data System (ADS)

Bliefernicht, J.; Bárdossy, A.

2009-04-01

It is well known that weather patterns tend to recur from time to time. This property of the atmosphere is used by analogue forecasting techniques. They have a long history in weather forecasting and there are many applications predicting hydrological variables at the local scale for different lead times. The basic idea of the technique is to identify past weather situations which are similar (analogue) to the predicted one and to take the local conditions of the analogues as forecast. But the forecast performance of the analogue method depends on user-defined criteria like the choice of the distance function and the size of the predictor domain. In this study we propose a new methodology of optimising both criteria by minimising the forecast error with simulated annealing. The performance of the methodology is demonstrated for the probability forecast of daily areal precipitation. It is compared with a traditional analogue forecasting algorithm, which is used operational as an element of a hydrological forecasting system. The study is performed for several meso-scale catchments located in the Rhine basin in Germany. The methodology is validated by a jack-knife method in a perfect prognosis framework for a period of 48 years (1958-2005). The predictor variables are derived from the NCEP/NCAR reanalysis data set. The Brier skill score and the economic value are determined to evaluate the forecast skill and value of the technique. In this presentation we will present the concept of the optimisation algorithm and the outcome of the comparison. It will be also demonstrated how a decision maker should apply a probability forecast to maximise the economic benefit from it.

Impact of cross-reference pricing on pharmaceutical prices: manufacturers' pricing strategies and price regulation.

PubMed

Stargardt, Tom; Schreyögg, Jonas

2006-01-01

Several EU countries are determining reimbursement prices of pharmaceuticals by cross-referencing prices of foreign countries. Our objective is to quantify the theoretical cross-border spill-over effects of cross-reference pricing schemes on pharmaceutical prices in the former EU-15 countries. An analytical model was developed estimating the impact of pharmaceutical price changes in Germany on pharmaceutical prices in other countries in the former EU-15 using cross-reference pricing. We differentiated between the direct impact (from referencing to Germany directly) and the indirect impact (from referencing to other countries that conduct their own cross-reference pricing schemes). The relationship between the direct and indirect impact of a price change depends mainly on the method applied to set reimbursement prices. When applying cross-reference pricing, the reimbursement price is either determined by the lowest of foreign prices (e.g. Portugal), the average of foreign prices (e.g. Ireland) or a weighted average of foreign prices (e.g. Italy). If the respective drug is marketed in all referenced countries and prices are regularly updated, a price reduction of 1.00 euro in Germany will reduce maximum reimbursement prices in the former EU-15 countries from 0.15 euros in Austria to 0.36 euros in Italy. On one side, the cross-border spill-over effects of price reductions are undoubtedly welcomed by decision makers and may be favourable to the healthcare system in general. On the other side, these cross-border spill-over effects also provide strong incentives for strategic product launches, launch delays and lobbying activities, and can affect the effectiveness of regulation. To avoid the negative effects of cross-reference pricing, a weighted index of prices from as many countries as possible should be used to determine reimbursement prices in order to reduce the direct and indirect impact of individual countries.

Global strategies to reduce the price of antiretroviral medicines: evidence from transactional databases

PubMed Central

Kaplan, Warren; King, Alexis C; Lawrence, Danielle A; Leufkens, Hubert G; Fox, Matthew P

2009-01-01

Abstract Objective To estimate the impact of global strategies, such as pooled procurement arrangements, third-party price negotiation and differential pricing, on reducing the price of antiretrovirals (ARVs), which currently hinders universal access to HIV/AIDS treatment. Methods We estimated the impact of global strategies to reduce ARV prices using data on 7253 procurement transactions (July 2002–October 2007) from databases hosted by WHO and the Global Fund to Fight AIDS, Tuberculosis and Malaria. Findings For 19 of 24 ARV dosage forms, we detected no association between price and volume purchased. For the other five ARVs, high-volume purchases were 4–21% less expensive than medium- or low-volume purchases. Nine of 13 generic ARVs were priced 6–36% lower when purchased under the Clinton Foundation HIV/AIDS Initiative (CHAI). Fifteen of 18 branded ARVs were priced 23–498% higher for differentially priced purchases compared with non-CHAI generic purchases. However, two branded, differentially priced ARVs were priced 63% and 73% lower, respectively, than generic non-CHAI equivalents. Conclusion Large purchase volumes did not necessarily result in lower ARV prices. Although current plans for pooled procurement will further increase purchase volumes, savings are uncertain and should be balanced against programmatic costs. Third-party negotiation by CHAI resulted in lower generic ARV prices. Generics were less expensive than differentially priced branded ARVs, except where little generic competition exists. Alternative strategies for reducing ARV prices, such as streamlining financial management systems, improving demand forecasting and removing barriers to generics, should be explored. PMID:19649366

Pricing a Protest: Forecasting the Dynamics of Civil Unrest Activity in Social Media.

PubMed

Goode, Brian J; Krishnan, Siddharth; Roan, Michael; Ramakrishnan, Naren

2015-01-01

Online social media activity can often be a precursor to disruptive events such as protests, strikes, and "occupy" movements. We have observed that such civil unrest can galvanize supporters through social networks and help recruit activists to their cause. Understanding the dynamics of social network cascades and extrapolating their future growth will enable an analyst to detect or forecast major societal events. Existing work has primarily used structural and temporal properties of cascades to predict their future behavior. But factors like societal pressure, alignment of individual interests with broader causes, and perception of expected benefits also affect protest participation in social media. Here we develop an analysis framework using a differential game theoretic approach to characterize the cost of participating in a cascade, and demonstrate how we can combine such cost features with classical properties to forecast the future behavior of cascades. Using data from Twitter, we illustrate the effectiveness of our models on the "Brazilian Spring" and Venezuelan protests that occurred in June 2013 and November 2013, respectively. We demonstrate how our framework captures both qualitative and quantitative aspects of how these uprisings manifest through the lens of tweet volume on Twitter social media.

New Local, National and Regional Cereal Price Indices for Improved Identification of Food Insecurity

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Tondel, Fabien; Thorne, Jennifer A.; Essam, Timothy; Mann, Bristol F.; Stabler, Blake; Eilerts, Gary

2011-01-01

Large price increases over a short time period can be indicative of a deteriorating food security situation. Food price indices developed by the United Nations Food and Agriculture Organization (FAO) are used to monitor food price trends at a global level, but largely reflect supply and demand conditions in export markets. However, reporting by the United States Agency for International Development (USAID)'s Famine Early Warning Systems Network (FEWS NET) indicates that staple cereal prices in many markets of the developing world, especially in surplus-producing areas, often have a delayed and variable response to international export market price trends. Here we present new price indices compiled for improved food security monitoring and assessment, and specifically for monitoring conditions of food access across diverse food insecure regions. We found that cereal price indices constructed using market prices within a food insecure region showed significant differences from the international cereals price, and had a variable price dispersion across markets within each marketshed. Using satellite-derived remote sensing information that estimates local production and the FAO Cereals Index as predictors, we were able to forecast movements of the local or national price indices in the remote, arid and semi-arid countries of the 38 countries examined. This work supports the need for improved decision-making about targeted aid and humanitarian relief, by providing earlier early warning of food security crises.

Peak load demand forecasting using two-level discrete wavelet decomposition and neural network algorithm

NASA Astrophysics Data System (ADS)

Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak

2010-02-01

This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.

Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics

PubMed Central

Ranco, Gabriele; Bordino, Ilaria; Bormetti, Giacomo; Caldarelli, Guido; Lillo, Fabrizio; Treccani, Michele

2016-01-01

The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users’ behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and daily price changes of a set of 100 highly capitalized US stocks traded in the period 2012–2013. Sentiment analysis or browsing activity when taken alone have very small or no predictive power. Conversely, when considering a news signal where in a given time interval we compute the average sentiment of the clicked news, weighted by the number of clicks, we show that for nearly 50% of the companies such signal Granger-causes hourly price returns. Our result indicates a “wisdom-of-the-crowd” effect that allows to exploit users’ activity to identify and weigh properly the relevant and surprising news, enhancing considerably the forecasting power of the news sentiment. PMID:26808833

Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics.

PubMed

Ranco, Gabriele; Bordino, Ilaria; Bormetti, Giacomo; Caldarelli, Guido; Lillo, Fabrizio; Treccani, Michele

2016-01-01

The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users' behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and daily price changes of a set of 100 highly capitalized US stocks traded in the period 2012-2013. Sentiment analysis or browsing activity when taken alone have very small or no predictive power. Conversely, when considering a news signal where in a given time interval we compute the average sentiment of the clicked news, weighted by the number of clicks, we show that for nearly 50% of the companies such signal Granger-causes hourly price returns. Our result indicates a "wisdom-of-the-crowd" effect that allows to exploit users' activity to identify and weigh properly the relevant and surprising news, enhancing considerably the forecasting power of the news sentiment.

Association of Reference Pricing with Drug Selection and Spending

PubMed Central

Robinson, James C.; Whaley, Christopher M.; Brown, Timothy T.

2017-01-01

BACKGROUND In the United States, prices for therapeutically similar drugs vary widely, which has prompted efforts by public and private insurers to steer patients toward the lower-priced options. Under reference pricing, the insurer or employer establishes a maximum contribution it will make toward the price of a drug or procedure, and the patient pays the remainder. METHODS We used difference-in-differences multivariable regression methods to analyze changes in prescriptions and pricing for 1302 drugs in 78 therapeutic classes in the United States, before and after implementation of reference pricing by an alliance of private employers. We assessed trends for the study group relative to those for an employee group that was not subject to reference pricing. The study included 1,122,741 prescriptions that were reimbursed during the period from 2010 through 2014. RESULTS Implementation of reference pricing was associated with a higher percentage of prescriptions that were filled for the lowest-priced reference drug within its therapeutic class (difference in probability, 7.0 percentage points; 95% confidence interval [CI], 4.0 to 9.9), a lower average price paid per prescription (−13.9%; 95% CI, −23.8 to −2.7), and a higher rate of copayment by patients (5.2%; 95% CI, 0.2 to 10.4) than in the comparison group. During the first 18 months after implementation, spending for employers was $1.34 million lower and the amount of copayments for employees was $0.12 million higher than in the comparison group. CONCLUSIONS Implementation of reference pricing was associated with significant changes in drug selection and spending for a population of patients covered by employment-based insurance in the United States. (Funded by the Agency for Healthcare Research and Quality and the Genentech Foundation.) PMID:28813219

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

NASA Astrophysics Data System (ADS)

Seibert, Mathias; Merz, Bruno; Apel, Heiko

2017-03-01

The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Niño and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42 % explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics

A statistical analysis of product prices in online markets

NASA Astrophysics Data System (ADS)

Mizuno, T.; Watanabe, T.

2010-08-01

We empirically investigate fluctuations in product prices in online markets by using a tick-by-tick price data collected from a Japanese price comparison site, and find some similarities and differences between product and asset prices. The average price of a product across e-retailers behaves almost like a random walk, although the probability of price increase/decrease is higher conditional on the multiple events of price increase/decrease. This is quite similar to the property reported by previous studies about asset prices. However, we fail to find a long memory property in the volatility of product price changes. Also, we find that the price change distribution for product prices is close to an exponential distribution, rather than a power law distribution. These two findings are in a sharp contrast with the previous results regarding asset prices. We propose an interpretation that these differences may stem from the absence of speculative activities in product markets; namely, e-retailers seldom repeat buy and sell of a product, unlike traders in asset markets.

Automated flare forecasting using a statistical learning technique

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Shih, Frank Y.; Jing, Ju; Wang, Hai-Min

2010-08-01

We present a new method for automatically forecasting the occurrence of solar flares based on photospheric magnetic measurements. The method is a cascading combination of an ordinal logistic regression model and a support vector machine classifier. The predictive variables are three photospheric magnetic parameters, i.e., the total unsigned magnetic flux, length of the strong-gradient magnetic polarity inversion line, and total magnetic energy dissipation. The output is true or false for the occurrence of a certain level of flares within 24 hours. Experimental results, from a sample of 230 active regions between 1996 and 2005, show the accuracies of a 24-hour flare forecast to be 0.86, 0.72, 0.65 and 0.84 respectively for the four different levels. Comparison shows an improvement in the accuracy of X-class flare forecasting.

Should we use seasonnal meteorological ensemble forecasts for hydrological forecasting? A case study for nordic watersheds in Canada.

NASA Astrophysics Data System (ADS)

Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert; Guay, Catherine

2017-04-01

reliability diagram. This study covers 10 nordic watersheds. We show that forecast performance according to the CRPS varies with lead-time but also with the period of the year. The raw forecasts from the ECMWF System4 display important biases for both temperature and precipitation, which need to be corrected. The linear scaling method is used for this purpose and is found effective. Bias correction improves forecasts performance, especially during the summer when the precipitations are over-estimated. According to the CRPS, bias corrected forecasts from System4 show performances comparable to those of the ESP system. However, the Ignorance score, which penalizes the lack of calibration (under-dispersive forecasts in this case) more severely than the CRPS, provides a different outlook for the comparison of the two systems. In fact, according to the Ignorance score, the ESP system outperforms forecasts based on System4 in most cases. This illustrates that the joint use of several metrics is crucial to assess the quality of a forecasts system thoroughly. Globally, ESP provide reliable forecasts which can be over-dispersed whereas bias corrected ECMWF System4 forecasts are sharper but at the risk of missing events.

A Prescription for Drug Formulary Evaluation: An Application of Price Indexes

PubMed Central

Glazer, Jacob; Huskamp, Haiden A.; McGuire, Thomas G.

2012-01-01

Existing economic approaches to the design and evaluation of health insurance do not readily apply to coverage decisions in the multi-tiered drug formularies characterizing drug coverage in private health insurance and Medicare. This paper proposes a method for evaluating a change in the value of a formulary to covered members based on the economic theory of price indexes. A formulary is cast as a set of demand-side prices, and our measure approximates the compensation (positive or negative) that would need to be paid to consumers to accept the new set of prices. The measure also incorporates any effect of the formulary change on plan drug acquisition costs and “offset effects” on non-drug services covered by the plan. Data needed to calculate formulary value are known or can be forecast by a health plan. We illustrate the method with data from a move from a two- to a three-tier formulary. PMID:23372543

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

USGS Publications Warehouse

Dietze, Michael C.; Fox, Andrew; Beck-Johnson, Lindsay; Betancourt, Julio L.; Hooten, Mevin B.; Jarnevich, Catherine S.; Keitt, Timothy H.; Kenney, Melissa A.; Laney, Christine M.; Larsen, Laurel G.; Loescher, Henry W.; Lunch, Claire K.; Pijanowski, Bryan; Randerson, James T.; Read, Emily; Tredennick, Andrew T.; Vargas, Rodrigo; Weathers, Kathleen C.; White, Ethan P.

2018-01-01

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Iterative near-term ecological forecasting: Needs, opportunities, and challenges.

PubMed

Dietze, Michael C; Fox, Andrew; Beck-Johnson, Lindsay M; Betancourt, Julio L; Hooten, Mevin B; Jarnevich, Catherine S; Keitt, Timothy H; Kenney, Melissa A; Laney, Christine M; Larsen, Laurel G; Loescher, Henry W; Lunch, Claire K; Pijanowski, Bryan C; Randerson, James T; Read, Emily K; Tredennick, Andrew T; Vargas, Rodrigo; Weathers, Kathleen C; White, Ethan P

2018-02-13

Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

7 CFR 1000.50 - Class prices, component prices, and advanced pricing factors.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing... advanced pricing factors. Class prices per hundredweight of milk containing 3.5 percent butterfat, component prices, and advanced pricing factors shall be as follows. The prices and pricing factors described...

Influenza forecasting in human populations: a scoping review.

PubMed

Chretien, Jean-Paul; George, Dylan; Shaman, Jeffrey; Chitale, Rohit A; McKenzie, F Ellis

2014-01-01

Forecasts of influenza activity in human populations could help guide key preparedness tasks. We conducted a scoping review to characterize these methodological approaches and identify research gaps. Adapting the PRISMA methodology for systematic reviews, we searched PubMed, CINAHL, Project Euclid, and Cochrane Database of Systematic Reviews for publications in English since January 1, 2000 using the terms "influenza AND (forecast* OR predict*)", excluding studies that did not validate forecasts against independent data or incorporate influenza-related surveillance data from the season or pandemic for which the forecasts were applied. We included 35 publications describing population-based (N = 27), medical facility-based (N = 4), and regional or global pandemic spread (N = 4) forecasts. They included areas of North America (N = 15), Europe (N = 14), and/or Asia-Pacific region (N = 4), or had global scope (N = 3). Forecasting models were statistical (N = 18) or epidemiological (N = 17). Five studies used data assimilation methods to update forecasts with new surveillance data. Models used virological (N = 14), syndromic (N = 13), meteorological (N = 6), internet search query (N = 4), and/or other surveillance data as inputs. Forecasting outcomes and validation metrics varied widely. Two studies compared distinct modeling approaches using common data, 2 assessed model calibration, and 1 systematically incorporated expert input. Of the 17 studies using epidemiological models, 8 included sensitivity analysis. This review suggests need for use of good practices in influenza forecasting (e.g., sensitivity analysis); direct comparisons of diverse approaches; assessment of model calibration; integration of subjective expert input; operational research in pilot, real-world applications; and improved mutual understanding among modelers and public health officials.

Influenza Forecasting in Human Populations: A Scoping Review

PubMed Central

Chretien, Jean-Paul; George, Dylan; Shaman, Jeffrey; Chitale, Rohit A.; McKenzie, F. Ellis

2014-01-01

Forecasts of influenza activity in human populations could help guide key preparedness tasks. We conducted a scoping review to characterize these methodological approaches and identify research gaps. Adapting the PRISMA methodology for systematic reviews, we searched PubMed, CINAHL, Project Euclid, and Cochrane Database of Systematic Reviews for publications in English since January 1, 2000 using the terms “influenza AND (forecast* OR predict*)”, excluding studies that did not validate forecasts against independent data or incorporate influenza-related surveillance data from the season or pandemic for which the forecasts were applied. We included 35 publications describing population-based (N = 27), medical facility-based (N = 4), and regional or global pandemic spread (N = 4) forecasts. They included areas of North America (N = 15), Europe (N = 14), and/or Asia-Pacific region (N = 4), or had global scope (N = 3). Forecasting models were statistical (N = 18) or epidemiological (N = 17). Five studies used data assimilation methods to update forecasts with new surveillance data. Models used virological (N = 14), syndromic (N = 13), meteorological (N = 6), internet search query (N = 4), and/or other surveillance data as inputs. Forecasting outcomes and validation metrics varied widely. Two studies compared distinct modeling approaches using common data, 2 assessed model calibration, and 1 systematically incorporated expert input. Of the 17 studies using epidemiological models, 8 included sensitivity analysis. This review suggests need for use of good practices in influenza forecasting (e.g., sensitivity analysis); direct comparisons of diverse approaches; assessment of model calibration; integration of subjective expert input; operational research in pilot, real-world applications; and improved mutual understanding among modelers and public health officials. PMID:24714027

Forecast errors in dust vertical distributions over Rome (Italy): Multiple particle size representation and cloud contributions

NASA Astrophysics Data System (ADS)

Kishcha, P.; Alpert, P.; Shtivelman, A.; Krichak, S. O.; Joseph, J. H.; Kallos, G.; Katsafados, P.; Spyrou, C.; Gobbi, G. P.; Barnaba, F.; Nickovic, S.; PéRez, C.; Baldasano, J. M.

2007-08-01

In this study, forecast errors in dust vertical distributions were analyzed. This was carried out by using quantitative comparisons between dust vertical profiles retrieved from lidar measurements over Rome, Italy, performed from 2001 to 2003, and those predicted by models. Three models were used: the four-particle-size Dust Regional Atmospheric Model (DREAM), the older one-particle-size version of the SKIRON model from the University of Athens (UOA), and the pre-2006 one-particle-size Tel Aviv University (TAU) model. SKIRON and DREAM are initialized on a daily basis using the dust concentration from the previous forecast cycle, while the TAU model initialization is based on the Total Ozone Mapping Spectrometer aerosol index (TOMS AI). The quantitative comparison shows that (1) the use of four-particle-size bins in the dust modeling instead of only one-particle-size bins improves dust forecasts; (2) cloud presence could contribute to noticeable dust forecast errors in SKIRON and DREAM; and (3) as far as the TAU model is concerned, its forecast errors were mainly caused by technical problems with TOMS measurements from the Earth Probe satellite. As a result, dust forecast errors in the TAU model could be significant even under cloudless conditions. The DREAM versus lidar quantitative comparisons at different altitudes show that the model predictions are more accurate in the middle part of dust layers than in the top and bottom parts of dust layers.

The price may not be right: the value of comparison shopping for prescription drugs.

PubMed

Arora, Sanjay; Sood, Neeraj; Terp, Sophie; Joyce, Geoffrey

2017-07-01

To measure variations in drug prices across and within zip codes that may reveal simple strategies to improve patients' access to prescribed medications. We compared drug prices at different types of pharmacies across and within local markets. In-store prices were compared with a Web-based service providing discount coupons for prescription medications. Prices were collected for 2 generic antibiotics because most patients have limited experience with them and are less likely to know the price ranges for them. Drug prices were obtained via telephone from 528 pharmacies in Los Angeles (LA) County, California, from July to August 2014. Online prices were collected from GoodRx, a popular Web-based service that aggregates available discounts and directly negotiates with retail outlets. Drug prices found at independent pharmacies and by using discount coupons available online were lower on average than at grocery, big-box, or chain drug stores for 2 widely prescribed antibiotics. The lowest-price prescription was offered at a grocery, big-box, or chain drug store in 6% of zip codes within the LA County area. Drug prices varied dramatically within a zip code, however, and were less expensive in lower-income areas. The average price difference within a zip code was $52 for levofloxacin and $17 for azithromycin. Price shopping for medications within a small geographic area can yield considerable cost savings for the uninsured and consumers in high-deductible health plans with high negotiated prices. Clinicians and patient advocates have an incentive to convey this information to patients to improve adherence to prescribed medicines and lower the financial burden of purchasing prescription drugs.

Using Heliospheric Imaging for Storm Forecasting - SMEI CME Observations as a Tool for Operational Forecasting at AFWA

NASA Astrophysics Data System (ADS)

Webb, D. F.; Johnston, J. C.; Fry, C. D.; Kuchar, T. A.

2008-12-01

is then expected to be about 3 hours after this 1 AU arrival time (AT). The prediction program is updated as more SMEI data become available. Currently when an appropriate solar event occurs, AFWA routinely runs the HAFv2 model to make a forecast of the shock and ejecta arrival times at Earth. SMEI data can be used to improve this prediction. The HAFv2 model can produce synthetic sky maps of predicted CME brightness for comparison with SMEI images. The forecaster uses SMEI imagery to observe and track the CME. The forecaster then measures the CME location and speed using the SMEI imagery and the HAFv2 synthetic sky maps. After comparing the SMEI and HAFv2 results, the forecaster can adjust a key input to HAFv2, such as the initial speed of the disturbance at the Sun or the mid-course speed. The forecaster then iteratively runs HAFv2 until the observed and forecast sky maps match. The final HAFv2 solution becomes the new forecast. When the CME/shock arrives at (or does not reach) Earth, the forecaster verifies the forecast and updates the forecast skill statistics. Eventually, we plan to develop a more automated version of this procedure.

Improved Anvil Forecasting

NASA Technical Reports Server (NTRS)

Lambert, Winifred C.

2000-01-01

This report describes the outcome of Phase 1 of the AMU's Improved Anvil Forecasting task. Forecasters in the 45th Weather Squadron and the Spaceflight Meteorology Group have found that anvil forecasting is a difficult task when predicting LCC and FR violations. The purpose of this task is to determine the technical feasibility of creating an anvil-forecasting tool. Work on this study was separated into three steps: literature search, forecaster discussions, and determination of technical feasibility. The literature search revealed no existing anvil-forecasting techniques. However, there appears to be growing interest in anvils in recent years. If this interest continues to grow, more information will be available to aid in developing a reliable anvil-forecasting tool. The forecaster discussion step revealed an array of methods on how better forecasting techniques could be developed. The forecasters have ideas based on sound meteorological principles and personal experience in forecasting and analyzing anvils. Based on the information gathered in the discussions with the forecasters, the conclusion of this report is that it is technically feasible at this time to develop an anvil forecasting technique that will significantly contribute to the confidence in anvil forecasts.

Monthly monsoon rainfall forecasting using artificial neural networks

NASA Astrophysics Data System (ADS)

Ganti, Ravikumar

2014-10-01

Indian agriculture sector heavily depends on monsoon rainfall for successful harvesting. In the past, prediction of rainfall was mainly performed using regression models, which provide reasonable accuracy in the modelling and forecasting of complex physical systems. Recently, Artificial Neural Networks (ANNs) have been proposed as efficient tools for modelling and forecasting. A feed-forward multi-layer perceptron type of ANN architecture trained using the popular back-propagation algorithm was employed in this study. Other techniques investigated for modeling monthly monsoon rainfall include linear and non-linear regression models for comparison purposes. The data employed in this study include monthly rainfall and monthly average of the daily maximum temperature in the North Central region in India. Specifically, four regression models and two ANN model's were developed. The performance of various models was evaluated using a wide variety of standard statistical parameters and scatter plots. The results obtained in this study for forecasting monsoon rainfalls using ANNs have been encouraging. India's economy and agricultural activities can be effectively managed with the help of the availability of the accurate monsoon rainfall forecasts.

Advanced inflow forecasting for a hydropower plant in an Alpine hydropower regulated catchment - coupling of operational and hydrological forecasts

NASA Astrophysics Data System (ADS)

Tilg, Anna-Maria; Schöber, Johannes; Huttenlau, Matthias; Messner, Jakob; Achleitner, Stefan

2017-04-01

Hydropower is a renewable energy source which can help to stabilize fluctuations in the volatile energy market. Especially pumped-storage infrastructures in the European Alps play an important role within the European energy grid system. Today, the runoff of rivers in the Alps is often influenced by cascades of hydropower infrastructures where the operational procedures are triggered by energy market demands, water deliveries and flood control aspects rather than by hydro-meteorological variables. An example for such a highly hydropower regulated river is the catchment of the river Inn in the Eastern European Alps, originating in the Engadin (Switzerland). A new hydropower plant is going to be built as transboundary project at the boarder of Switzerland and Austria using the water of the Inn River. For the operation, a runoff forecast to the plant is required. The challenge in this case is that a high proportion of runoff is turbine water from an upstream situated hydropower cascade. The newly developed physically based hydrological forecasting system is mainly capable to cover natural hydrological runoff processes caused by storms and snow melt but can model only a small degree of human impact. These discontinuous parts of the runoff downstream of the pumped storage are described by means of an additional statistical model which has been developed. The main goal of the statistical model is to forecast the turbine water up to five days in advance. The lead time of the data driven model exceeds the lead time of the used energy production forecast. Additionally, the amount of turbine water is linked to the need of electricity production and the electricity price. It has been shown that especially the parameters day-ahead prognosis of the energy production and turbine inflow of the previous week are good predictors and are therefore used as input parameters for the model. As the data is restricted due to technical conditions, so-called Tobit models have been used to

A 30-day forecast experiment with the GISS model and updated sea surface temperatures

NASA Technical Reports Server (NTRS)

Spar, J.; Atlas, R.; Kuo, E.

1975-01-01

The GISS model was used to compute two parallel global 30-day forecasts for the month January 1974. In one forecast, climatological January sea surface temperatures were used, while in the other observed sea temperatures were inserted and updated daily. A comparison of the two forecasts indicated no clear-cut beneficial effect of daily updating of sea surface temperatures. Despite the rapid decay of daily predictability, the model produced a 30-day mean forecast for January 1974 that was generally superior to persistence and climatology when evaluated over either the globe or the Northern Hemisphere, but not over smaller regions.

Forecasting stochastic neural network based on financial empirical mode decomposition.

PubMed

Wang, Jie; Wang, Jun

2017-06-01

In an attempt to improve the forecasting accuracy of stock price fluctuations, a new one-step-ahead model is developed in this paper which combines empirical mode decomposition (EMD) with stochastic time strength neural network (STNN). The EMD is a processing technique introduced to extract all the oscillatory modes embedded in a series, and the STNN model is established for considering the weight of occurrence time of the historical data. The linear regression performs the predictive availability of the proposed model, and the effectiveness of EMD-STNN is revealed clearly through comparing the predicted results with the traditional models. Moreover, a new evaluated method (q-order multiscale complexity invariant distance) is applied to measure the predicted results of real stock index series, and the empirical results show that the proposed model indeed displays a good performance in forecasting stock market fluctuations. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Comparison of Conventional Linear Regression Methods and Neural Networks for Forecasting Educational Spending.

ERIC Educational Resources Information Center

Baker, Bruce D.; Richards, Craig E.

1999-01-01

Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…

Using Enabling Technologies to Facilitate the Comparison of Satellite Observations with the Model Forecasts for Hurricane Study

NASA Astrophysics Data System (ADS)

Li, P.; Knosp, B.; Hristova-Veleva, S. M.; Niamsuwan, N.; Johnson, M. P.; Shen, T. P. J.; Tanelli, S.; Turk, J.; Vu, Q. A.

2014-12-01

Due to their complexity and volume, the satellite data are underutilized in today's hurricane research and operations. To better utilize these data, we developed the JPL Tropical Cyclone Information System (TCIS) - an Interactive Data Portal providing fusion between Near-Real-Time satellite observations and model forecasts to facilitate model evaluation and improvement. We have collected satellite observations and model forecasts in the Atlantic Basin and the East Pacific for the hurricane seasons since 2010 and supported the NASA Airborne Campaigns for Hurricane Study such as the Genesis and Rapid Intensification Processes (GRIP) in 2010 and the Hurricane and Severe Storm Sentinel (HS3) from 2012 to 2014. To enable the direct inter-comparisons of the satellite observations and the model forecasts, the TCIS was integrated with the NASA Earth Observing System Simulator Suite (NEOS3) to produce synthetic observations (e.g. simulated passive microwave brightness temperatures) from a number of operational hurricane forecast models (HWRF and GFS). An automated process was developed to trigger NEOS3 simulations via web services given the location and time of satellite observations, monitor the progress of the NEOS3 simulations, display the synthetic observation and ingest them into the TCIS database when they are done. In addition, three analysis tools, the joint PDF analysis of the brightness temperatures, ARCHER for finding the storm-center and the storm organization and the Wave Number Analysis tool for storm asymmetry and morphology analysis were integrated into TCIS to provide statistical and structural analysis on both observed and synthetic data. Interactive tools were built in the TCIS visualization system to allow the spatial and temporal selections of the datasets, the invocation of the tools with user specified parameters, and the display and the delivery of the results. In this presentation, we will describe the key enabling technologies behind the design of

Evaluation of health plan member use of an online prescription drug price comparison tool.

PubMed

Carroll, Norman V; Mitchell, Matthew P; Cannon, H Eric; York, Bryan W York; Oscar, Robert S

2010-01-01

Health plans have implemented tiered copayment systems to incentivize members to use less expensive medications. However, members need drug price information to make comparisons among therapeutic alternatives. Many health plans and pharmacy benefit management companies have implemented online prescription drug price comparison tools to provide such information. There has been little published evaluation of these tools. To evaluate use of an online price comparison tool- MyPharmacyTools (MPT)- by the measures of (a) the extent to which the tool was used, (b) changes in use over the first year after implementation, and (c) the types of members who were most likely to use the tool. Data were provided by a 500,000-member integrated health plan with approximately 156,250 enrolled families. The sample included only families with continuous eligibility for all members from July 1, 2006, through June 30, 2008; use of 1 of 7 common copayment structures; and use of the pharmacy benefit in every quarter of the study period. Data collected on each member, using pharmacy claims for the time period July 1, 2007, through June 30, 2008, included annual drug costs (total, out-of-pocket, plan-paid, and mail order) and number of unique drugs and unique generic drugs taken during the third quarter of 2007. Data collected also included whether the member had each of several selected chronic diseases (as inferred from drug claims for the third quarter of 2007) and demographics. Age, gender, and family size were taken from eligibility files. Other demographic data were imputed to members from the demographics of the ZIP code in which they resided. MPT was made available to members on July 1, 2007. Use of MPT was measured as the number of times members logged into the site for each quarter during the subsequent year. Statistical analyses were conducted at the family rather than at the individual level, and families were defined as users if any family member used MPT at least once during

Can we use Earth Observations to improve monthly water level forecasts?

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2017-12-01

Dynamical-statistical hydrologic forecasting approaches benefit from different strengths in comparison with traditional hydrologic forecasting systems: they are computationally efficient, can integrate and `learn' from a broad selection of input data (e.g., General Circulation Model (GCM) forecasts, Earth Observation time series, teleconnection patterns), and can take advantage of recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques). Recent efforts to develop a dynamical-statistical ensemble approach for forecasting seasonal streamflow using both GCM forecasts and changing land cover have shown promising results over the U.S. Midwest. Here, we use climate forecasts from several GCMs of the North American Multi Model Ensemble (NMME) alongside 15-minute stage time series from the National River Flow Archive (NRFA) and land cover classes extracted from the European Space Agency's Climate Change Initiative 300 m annual Global Land Cover time series. With these data, we conduct systematic long-range probabilistic forecasting of monthly water levels in UK catchments over timescales ranging from one to twelve months ahead. We evaluate the improvement in model fit and model forecasting skill that comes from using land cover classes as predictors in the models. This work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards from space using data science techniques.

The impact of alternative pricing methods for drugs in California Workers' Compensation System: Fee-schedule pricing.

PubMed

Wilson, Leslie; Turkistani, Fatema A; Huang, Wei; Tran, Dang M; Lin, Tracy Kuo

2018-01-01

California's Workers' Compensation System (CAWCS) Department of Industrial Relations questioned the adequacy of the current Medi-Cal fee-schedule pricing and requested analysis of alternatives that maximize price availability and maintain budget neutrality. To compare CAWCS pharmacy-dispensed (PD) drug prices under alternative fee schedules, and identify combinations of alternative benchmarks that have prices available for the largest percentage of PD drugs and that best reach budget neutrality. Claims transaction-level data (2011-2013) from CAWCS were used to estimate total annual PD pharmaceutical payments. Medi-Cal pricing data was from the Workman's Compensation Insurance System (WCIS). Average Wholesale Prices (AWP), Wholesale Acquisition Costs (WAC), Direct Prices (DP), Federal Upper Limit (FUL) prices, and National Average Drug Acquisition Costs (NADAC) were from Medi-Span. We matched National Drug Codes (NDCs), pricing dates, and drug quantity for comparisons. We report pharmacy-dispensed (PD) claims frequency, reimbursement matching rate, and paid costs by CAWCS as the reference price against all alternative price benchmarks. Of 12,529,977 CAWCS claims for pharmaceutical products 11.6% (1,462,814) were for PD drugs. Prescription drug cost for CAWCS was over $152M; $63.9M, $47.9M, and $40.6M in 2011-2013. Ninety seven percent of these CAWCS PD claims had a Medi-Cal price. Alternative mechanisms provided a price for fewer claims; NADAC 94.23%, AWP 90.94%, FUL 73.11%, WAC 66.98%, and DP 14.33%. Among CAWCS drugs with no Medi-Cal price in PD claims, AWP, WAC, NADAC, DP, and FUL provided prices for 96.7%, 63.14%, 24.82%, 20.83%, and 15.08% of claims. Overall CAWCS paid 100.52% of Medi-Cal, 60% of AWP, 97% of WAC, 309.53% of FUL, 103.83% of DP, and 136.27% of NADAC. CAWCS current Medi-Cal fee-schedule price list for PD drugs is more complete than all alternative fee-schedules. However, all reimbursement approaches would require combinations of pricing benchmarks

Supplemental Tables to the Annual Energy Outlook

EIA Publications

2017-01-01

The Annual Energy Outlook (AEO) Supplemental tables were generated for the reference case of the AEO using the National Energy Modeling System, a computer-based model which produces annual projections of energy markets. Most of the tables were not published in the AEO, but contain regional and other more detailed projections underlying the AEO projections.

Impact of archeomagnetic field model data on modern era geomagnetic forecasts

NASA Astrophysics Data System (ADS)

Tangborn, Andrew; Kuang, Weijia

2018-03-01

A series of geomagnetic data assimilation experiments have been carried out to demonstrate the impact of assimilating archeomagnetic data via the CALS3k.4 geomagnetic field model from the period between 10 and 1590 CE. The assimilation continues with the gufm1 model from 1590 to 1990 and CM4 model from 1990 to 2000 as observations, and comparisons between these models and the geomagnetic forecasts are used to determine an optimal maximum degree for the archeomagnetic observations, and to independently estimate errors for these observations. These are compared with an assimilation experiment that uses the uncertainties provided with CALS3k.4. Optimal 20 year forecasts in 1990 are found when the Gauss coefficients up to degree 3 are assimilated. In addition we demonstrate how a forecast and observation bias correction scheme could be used to reduce bias in modern era forecasts. Initial experiments show that this approach can reduce modern era forecast biases by as much as 50%.

Evolving forecasting classifications and applications in health forecasting

PubMed Central

Soyiri, Ireneous N; Reidpath, Daniel D

2012-01-01

Health forecasting forewarns the health community about future health situations and disease episodes so that health systems can better allocate resources and manage demand. The tools used for developing and measuring the accuracy and validity of health forecasts commonly are not defined although they are usually adapted forms of statistical procedures. This review identifies previous typologies used in classifying the forecasting methods commonly used in forecasting health conditions or situations. It then discusses the strengths and weaknesses of these methods and presents the choices available for measuring the accuracy of health-forecasting models, including a note on the discrepancies in the modes of validation. PMID:22615533

The Multi-Frequency Correlation Between Eua and sCER Futures Prices: Evidence from the Emd Approach

NASA Astrophysics Data System (ADS)

Zhang, Yue-Jun; Huang, Yi-Song

2015-05-01

Currently European Union Allowances (EUA) and secondary Certified Emission Reduction (sCER) have become two dominant carbon trading assets for investors and their linkage attracts much attention from academia and practitioners in recent years. Under this circumstance, we use the empirical mode decomposition (EMD) approach to decompose the two carbon futures contract prices and discuss their correlation from the multi-frequency perspective. The empirical results indicate that, first, the EUA and sCER futures price movements can be divided into those triggered by the long-term, medium-term and short-term market impacts. Second, the price movements in the EUA and sCER futures markets are primarily caused by the long-term impact, while the short-term impact can only explain a small fraction. Finally, the long-term (short-term) effect on EUA prices is statistically uncorrelated with the short-term (long-term) effect of sCER prices, and there is a medium or strong lead-and-lag correlation between the EUA and sCER price components with the same time scales. These results may provide some important insights of price forecast and arbitraging activities for carbon futures market investors, analysts and regulators.

Evaluation of the Plant-Craig stochastic convection scheme in an ensemble forecasting system

NASA Astrophysics Data System (ADS)

Keane, R. J.; Plant, R. S.; Tennant, W. J.

2015-12-01

The Plant-Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic element only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant-Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant-Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

A comparison of water vapor quantities from model short-range forecasts and ARM observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hnilo, J J

2006-03-17

Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the 'Merged-sounding' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGPmore » and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.« less

Summary Impacts of Modeled Provisions of the 2003 Conference Energy Bill

EIA Publications

2004-01-01

This service report was undertaken at the February 2, 2004, request of Senator John Sununu to perform an assessment of the Conference Energy Bill of 2003. This report summarizes the CEB provisions that can be analyzed using the National Energy Modeling System (NEMS) and have the potential to affect energy consumption, supply, and prices. The impacts are estimated by comparing the projections with the CEB provisions to the AEO2004 Reference Case.

Economic assessment of flood forecasts for a risk-averse decision-maker

NASA Astrophysics Data System (ADS)

Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier-Filion, Thomas-Charles

2017-04-01

A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. It has also been suggested in past studies that ensemble forecasts might possess a greater economic value than deterministic forecasts. However, the vast majority of recent hydro-economic literature is based on the cost-loss ratio framework, which might be appealing for its simplicity and intuitiveness. One important drawback of the cost-loss ratio is that it implicitly assumes a risk-neutral decision maker. By definition, a risk-neutral individual is indifferent to forecasts' sharpness: as long as forecasts agree with observations on average, the risk-neutral individual is satisfied. A risk-averse individual, however, is sensitive to the level of precision (sharpness) of forecasts. This person is willing to pay to increase his or her certainty about future events. In fact, this is how insurance companies operate: the probability of seeing one's house burn down is relatively low, so the expected cost related to such event is also low. However, people are willing to buy insurance to avoid the risk, however small, of loosing everything. Similarly, in a context where people's safety and property is at stake, the typical decision maker is more risk-averse than risk-neutral. Consequently, the cost-loss ratio is not the most appropriate tool to assess the economic value of flood forecasts. This presentation describes a more realistic framework for assessing the economic value of such forecasts for flood mitigation purposes. Borrowing from economics, the Constant Absolute Risk Aversion utility function (CARA) is the central tool of this new framework. Utility functions allow explicitly accounting for the level of risk aversion of the decision maker and fully exploiting the information related to ensemble forecasts' uncertainty. Three concurrent ensemble streamflow forecasting systems are compared in terms of quality (comparison with

Forecasting Container Throughput at the Doraleh Port in Djibouti through Time Series Analysis

NASA Astrophysics Data System (ADS)

Mohamed Ismael, Hawa; Vandyck, George Kobina

The Doraleh Container Terminal (DCT) located in Djibouti has been noted as the most technologically advanced container terminal on the African continent. DCT's strategic location at the crossroads of the main shipping lanes connecting Asia, Africa and Europe put it in a unique position to provide important shipping services to vessels plying that route. This paper aims to forecast container throughput through the Doraleh Container Port in Djibouti by Time Series Analysis. A selection of univariate forecasting models has been used, namely Triple Exponential Smoothing Model, Grey Model and Linear Regression Model. By utilizing the above three models and their combination, the forecast of container throughput through the Doraleh port was realized. A comparison of the different forecasting results of the three models, in addition to the combination forecast is then undertaken, based on commonly used evaluation criteria Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). The study found that the Linear Regression forecasting Model was the best prediction method for forecasting the container throughput, since its forecast error was the least. Based on the regression model, a ten (10) year forecast for container throughput at DCT has been made.

Ozone distributions over southern Lake Michigan: comparisons between ferry-based observations, shoreline-based DOAS observations and model forecasts

NASA Astrophysics Data System (ADS)

Cleary, P. A.; Fuhrman, N.; Schulz, L.; Schafer, J.; Fillingham, J.; Bootsma, H.; McQueen, J.; Tang, Y.; Langel, T.; McKeen, S.; Williams, E. J.; Brown, S. S.

2015-05-01

Air quality forecast models typically predict large summertime ozone abundances over water relative to land in the Great Lakes region. While each state bordering Lake Michigan has dedicated monitoring systems, offshore measurements have been sparse, mainly executed through specific short-term campaigns. This study examines ozone abundances over Lake Michigan as measured on the Lake Express ferry, by shoreline differential optical absorption spectroscopy (DOAS) observations in southeastern Wisconsin and as predicted by the Community Multiscale Air Quality (CMAQ) model. From 2008 to 2009 measurements of O3, SO2, NO2 and formaldehyde were made in the summertime by DOAS at a shoreline site in Kenosha, WI. From 2008 to 2010 measurements of ambient ozone were conducted on the Lake Express, a high-speed ferry that travels between Milwaukee, WI, and Muskegon, MI, up to six times daily from spring to fall. Ferry ozone observations over Lake Michigan were an average of 3.8 ppb higher than those measured at shoreline in Kenosha, with little dependence on position of the ferry or temperature and with greatest differences during evening and night. Concurrent 1-48 h forecasts from the CMAQ model in the upper Midwestern region surrounding Lake Michigan were compared to ferry ozone measurements, shoreline DOAS measurements and Environmental Protection Agency (EPA) station measurements. The bias of the model O3 forecast was computed and evaluated with respect to ferry-based measurements. Trends in the bias with respect to location and time of day were explored showing non-uniformity in model bias over the lake. Model ozone bias was consistently high over the lake in comparison to land-based measurements, with highest biases for 25-48 h after initialization.

Evaluation of precipitation forecasts from 3D-Var and hybrid GSI-based system during Indian summer monsoon 2015

NASA Astrophysics Data System (ADS)

Singh, Sanjeev Kumar; Prasad, V. S.

2018-02-01

This paper presents a systematic investigation of medium-range rainfall forecasts from two versions of the National Centre for Medium Range Weather Forecasting (NCMRWF)-Global Forecast System based on three-dimensional variational (3D-Var) and hybrid analysis system namely, NGFS and HNGFS, respectively, during Indian summer monsoon (June-September) 2015. The NGFS uses gridpoint statistical interpolation (GSI) 3D-Var data assimilation system, whereas HNGFS uses hybrid 3D ensemble-variational scheme. The analysis includes the evaluation of rainfall fields and comparisons of rainfall using statistical score such as mean precipitation, bias, correlation coefficient, root mean square error and forecast improvement factor. In addition to these, categorical scores like Peirce skill score and bias score are also computed to describe particular aspects of forecasts performance. The comparison results of mean precipitation reveal that both the versions of model produced similar large-scale feature of Indian summer monsoon rainfall for day-1 through day-5 forecasts. The inclusion of fully flow-dependent background error covariance significantly improved the wet biases in HNGFS over the Indian Ocean. The forecast improvement factor and Peirce skill score in the HNGFS have also found better than NGFS for day-1 through day-5 forecasts.

Hybrid Forecasting of Daily River Discharges Considering Autoregressive Heteroscedasticity

NASA Astrophysics Data System (ADS)

Szolgayová, Elena Peksová; Danačová, Michaela; Komorniková, Magda; Szolgay, Ján

2017-06-01

It is widely acknowledged that in the hydrological and meteorological communities, there is a continuing need to improve the quality of quantitative rainfall and river flow forecasts. A hybrid (combined deterministic-stochastic) modelling approach is proposed here that combines the advantages offered by modelling the system dynamics with a deterministic model and a deterministic forecasting error series with a data-driven model in parallel. Since the processes to be modelled are generally nonlinear and the model error series may exhibit nonstationarity and heteroscedasticity, GARCH-type nonlinear time series models are considered here. The fitting, forecasting and simulation performance of such models have to be explored on a case-by-case basis. The goal of this paper is to test and develop an appropriate methodology for model fitting and forecasting applicable for daily river discharge forecast error data from the GARCH family of time series models. We concentrated on verifying whether the use of a GARCH-type model is suitable for modelling and forecasting a hydrological model error time series on the Hron and Morava Rivers in Slovakia. For this purpose we verified the presence of heteroscedasticity in the simulation error series of the KLN multilinear flow routing model; then we fitted the GARCH-type models to the data and compared their fit with that of an ARMA - type model. We produced one-stepahead forecasts from the fitted models and again provided comparisons of the model's performance.

The Price and Purity of Illicit Drugs: 1981-2007

DTIC Science & Technology

2008-10-01

categorizations of marijuana, i.e., domestic, Mexican, Canadian, and hydroponic . Comparisons of the NDIC data to 2005 STRIDE bulk prices for marijuana, which are...variations across different NDIC categorizations of marijuana, i.e., domestic, Mexican, Canadian, and hydroponic . Comparisons of the NDIC data to 2005

The Healing Effect of Arnebia Euchroma Ointment versus Silver Sulfadiazine on Burn Wounds in Rat

PubMed Central

Nasiri, Ebrahim; Hosseinimehr, Seyed Jalal; Azadbakht, Mohammad; Akbari, Jafar; Enayati-Fard, Reza; Azizi, Sohail; Azadbakht, Masoud

2015-01-01

BACKGROUND Burn is still a majordevastating condition in emergency medicine departments among both genders and all age groups in all developed and developing countries, leading to physical, psychological scars and economical burden. The present study aimed to determine the healing effect of topical treatment with Arnebia euchroma on second-degree burn wound in rats. METHODS Fifty rats were divided into 4 equal groups receiving the ointment base, normal saline (NS), standard 1% silver sulfadiazine (SSD), and 5% and 10% Arnebia euchroma ointments (AEO). The mean of burn area, percentage of wound contraction, histopathological and bacteriological assessments in the injured area were dtermined during the study. RESULTS Average area of wound on the 10th day was 10.2±2.3, 8.4±2.6, 12.4±2.5, 5.9±2.2 and 5.7±2 cm2 for ointment base, NS, 1% SSD, and 5% and 10% AEO, respectively. Wound size was significantly lower in 10% AEO than 1% SSD and control groups on the 10th day post-burn injury. On day 11, the percentage of wound contraction in 5% and 10% AEO was 53.9%±14.7% and 55.9±10.5% which was more than 1% SSD (15.3±10.8%). The collagen fibers were well formed and horizontally-oriented in 5% and 10% AEO groups when compared with other groups. CONCLUSION Arnebia euchroma ointment was an effective treatment for healing of burn wounds in comparison with SSD and can be regarded as an alternative topical treatment for burn wounds. PMID:26284182

A generalized approach to wheat yield forecasting using earth observations: Data considerations, application and relevance

NASA Astrophysics Data System (ADS)

Becker-Reshef, Inbal

In recent years there has been a dramatic increase in the demand for timely, comprehensive global agricultural intelligence. The issue of food security has rapidly risen to the top of government agendas around the world as the recent lack of food access led to unprecedented food prices, hunger, poverty, and civil conflict. Timely information on global crop production is indispensable for combating the growing stress on the world's crop production, for stabilizing food prices, developing effective agricultural policies, and for coordinating responses to regional food shortages. Earth Observations (EO) data offer a practical means for generating such information as they provide global, timely, cost-effective, and synoptic information on crop condition and distribution. Their utility for crop production forecasting has long been recognized and demonstrated across a wide range of scales and geographic regions. Nevertheless it is widely acknowledged that EO data could be better utilized within the operational monitoring systems and thus there is a critical need for research focused on developing practical robust methods for agricultural monitoring. Within this context this dissertation focused on advancing EO-based methods for crop yield forecasting and on demonstrating the potential relevance for adopting EO-based crop forecasts for providing timely reliable agricultural intelligence. This thesis made contributions to this field by developing and testing a robust EO-based method for wheat production forecasting at state to national scales using available and easily accessible data. The model was developed in Kansas (KS) using coarse resolution normalized difference vegetation index (NDVI) time series data in conjunction with out-of-season wheat masks and was directly applied in Ukraine to assess its transferability. The model estimated yields within 7% in KS and 10% in Ukraine of final estimates 6 weeks prior to harvest. The relevance of adopting such methods to

Price and consumption of tobacco.

PubMed

Singh, Virendra; Sharma, Bharat Bhushan; Saxena, Puneet; Meena, Hardayal; Mangal, Daya Krishan

2012-07-01

It is thought that price increase in tobacco products leads to reduced consumption. Though many studies have substantiated this concept, it has not been well studied in India. Recently, price of tobacco products was increased due to ban on plastic sachets of chewing tobacco and increased tax in Rajasthan. This study was designed to evaluate the effect of price rise on overall consumption of tobacco in Jaipur city, Rajasthan. This study was carried out in Jaipur city. Two-staged stratified sampling was used. In the first phase of study, cost and consumption of various tobacco products in the months of February and April were enquired from 25 retail tobacco shops. In the second phase, tobacco consumption was enquired from 20 consecutive consumers purchasing any tobacco product from all the above retail tobacco shops. The data were statistically analyzed using descriptive statistics and paired "t" test. The comparison of prices of tobacco products between February and April revealed that the price of cigarette, bidi, and chewing tobacco has increased by 19%, 21%, and 68%, respectively. Average decrease in sales of cigarettes, bidi, and chewing tobacco at shops included in the study were 14%, 23%, and 38%, respectively. The consumers purchasing tobacco also reported decreased consumption. Chewing tobacco showed the maximum reduction (21%). Consumption of cigarette and bidi has also reduced by 15% and 13%, respectively. It may be concluded that reduction in consumption is associated with increased price of tobacco products. Reduced consumption is comparative to the magnitude of price increase.

Price and consumption of tobacco

PubMed Central

Singh, Virendra; Sharma, Bharat Bhushan; Saxena, Puneet; Meena, Hardayal; Mangal, Daya Krishan

2012-01-01

Background: It is thought that price increase in tobacco products leads to reduced consumption. Though many studies have substantiated this concept, it has not been well studied in India. Recently, price of tobacco products was increased due to ban on plastic sachets of chewing tobacco and increased tax in Rajasthan. This study was designed to evaluate the effect of price rise on overall consumption of tobacco in Jaipur city, Rajasthan. Materials and Methods: This study was carried out in Jaipur city. Two-staged stratified sampling was used. In the first phase of study, cost and consumption of various tobacco products in the months of February and April were enquired from 25 retail tobacco shops. In the second phase, tobacco consumption was enquired from 20 consecutive consumers purchasing any tobacco product from all the above retail tobacco shops. The data were statistically analyzed using descriptive statistics and paired “t” test. Results: The comparison of prices of tobacco products between February and April revealed that the price of cigarette, bidi, and chewing tobacco has increased by 19%, 21%, and 68%, respectively. Average decrease in sales of cigarettes, bidi, and chewing tobacco at shops included in the study were 14%, 23%, and 38%, respectively. The consumers purchasing tobacco also reported decreased consumption. Chewing tobacco showed the maximum reduction (21%). Consumption of cigarette and bidi has also reduced by 15% and 13%, respectively. Conclusion: It may be concluded that reduction in consumption is associated with increased price of tobacco products. Reduced consumption is comparative to the magnitude of price increase. PMID:22919157

20 CFR 435.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NON-PROFIT ORGANIZATIONS, AND... every procurement action. Price analysis may be accomplished in various ways, including the comparison...

20 CFR 435.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NON-PROFIT ORGANIZATIONS, AND... every procurement action. Price analysis may be accomplished in various ways, including the comparison...

20 CFR 435.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NON-PROFIT ORGANIZATIONS, AND... every procurement action. Price analysis may be accomplished in various ways, including the comparison...

20 CFR 435.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NON-PROFIT ORGANIZATIONS, AND... every procurement action. Price analysis may be accomplished in various ways, including the comparison...

Mixture EMOS model for calibrating ensemble forecasts of wind speed.

PubMed

Baran, S; Lerch, S

2016-03-01

Ensemble model output statistics (EMOS) is a statistical tool for post-processing forecast ensembles of weather variables obtained from multiple runs of numerical weather prediction models in order to produce calibrated predictive probability density functions. The EMOS predictive probability density function is given by a parametric distribution with parameters depending on the ensemble forecasts. We propose an EMOS model for calibrating wind speed forecasts based on weighted mixtures of truncated normal (TN) and log-normal (LN) distributions where model parameters and component weights are estimated by optimizing the values of proper scoring rules over a rolling training period. The new model is tested on wind speed forecasts of the 50 member European Centre for Medium-range Weather Forecasts ensemble, the 11 member Aire Limitée Adaptation dynamique Développement International-Hungary Ensemble Prediction System ensemble of the Hungarian Meteorological Service, and the eight-member University of Washington mesoscale ensemble, and its predictive performance is compared with that of various benchmark EMOS models based on single parametric families and combinations thereof. The results indicate improved calibration of probabilistic and accuracy of point forecasts in comparison with the raw ensemble and climatological forecasts. The mixture EMOS model significantly outperforms the TN and LN EMOS methods; moreover, it provides better calibrated forecasts than the TN-LN combination model and offers an increased flexibility while avoiding covariate selection problems. © 2016 The Authors Environmetrics Published by JohnWiley & Sons Ltd.

Price differentiation and transparency in the global pharmaceutical marketplace.

PubMed

Ridley, David B

2005-01-01

Pharmaceutical manufacturers have increased the availability of their products and sometimes increased their own financial returns by charging lower prices outside of the US and by discounting to lower-income patients in the US. Examples include discounted HIV-AIDS drugs in developing countries and pharmaceutical manufacturers' discount cards in the US. Representatives of some international organisations argue that the price reductions are insufficient to make the medications widely available to lower-income patients. The WHO advocates both differential pricing and price transparency. While its efforts are well meaning, this paper identifies six concerns about its methods of comparing the price of a given molecule across manufacturers and across countries. More significantly, the WHO efforts to increase transparency are likely to lead to less price differentiation and less access to innovative pharmaceuticals. An important reason why manufacturers are reluctant to charge lower prices in lower-income countries is that they fear that such low prices will undermine the prices they charge to higher-income consumers. International organisations should not facilitate transparency but should dissuade governments from making price comparisons and basing their prices on those of lower-income countries. Furthermore, they should endeavour to keep low-priced and free drugs in the hands of the low-income consumers for which they were intended.

Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

NASA Technical Reports Server (NTRS)

Wang, Yao; Sridhar, Banavar

2010-01-01

intensity and location for center forecast are relatively low. For example, 1-hour forecast intensity and horizontal location errors for ZDC center were about 0.12 and 0.13. However, the correlation between sector 1-hour forecast and actual weather coverage was weak, for sector ZDC32, about 32% of the total variation of observation weather intensity was unexplained by forecast; the sector horizontal location error was about 0.10. The paper also introduces an approach to estimate the sector three-dimensional actual weather coverage by using multiple sector forecasts, which turned out to produce better predictions. Using Multiple Linear Regression (MLR) model for this approach, the correlations between actual observation and the multiple sector forecast model prediction improved by several percents at 95% confidence level in comparison with single sector forecast.

A comparison of the stochastic and machine learning approaches in hydrologic time series forecasting

NASA Astrophysics Data System (ADS)

Kim, T.; Joo, K.; Seo, J.; Heo, J. H.

2016-12-01

Hydrologic time series forecasting is an essential task in water resources management and it becomes more difficult due to the complexity of runoff process. Traditional stochastic models such as ARIMA family has been used as a standard approach in time series modeling and forecasting of hydrological variables. Due to the nonlinearity in hydrologic time series data, machine learning approaches has been studied with the advantage of discovering relevant features in a nonlinear relation among variables. This study aims to compare the predictability between the traditional stochastic model and the machine learning approach. Seasonal ARIMA model was used as the traditional time series model, and Random Forest model which consists of decision tree and ensemble method using multiple predictor approach was applied as the machine learning approach. In the application, monthly inflow data from 1986 to 2015 of Chungju dam in South Korea were used for modeling and forecasting. In order to evaluate the performances of the used models, one step ahead and multi-step ahead forecasting was applied. Root mean squared error and mean absolute error of two models were compared.

Forecasting of global solar radiation using anfis and armax techniques

NASA Astrophysics Data System (ADS)

Muhammad, Auwal; Gaya, M. S.; Aliyu, Rakiya; Aliyu Abdulkadir, Rabi'u.; Dauda Umar, Ibrahim; Aminu Yusuf, Lukuman; Umar Ali, Mudassir; Khairi, M. T. M.

2018-01-01

Procurement of measuring device, maintenance cost coupled with calibration of the instrument contributed to the difficulty in forecasting of global solar radiation in underdeveloped countries. Most of the available regressional and mathematical models do not capture well the behavior of the global solar radiation. This paper presents the comparison of Adaptive Neuro Fuzzy Inference System (ANFIS) and Autoregressive Moving Average with eXogenous term (ARMAX) in forecasting global solar radiation. Full-Scale (experimental) data of Nigerian metrological agency, Sultan Abubakar III international airport Sokoto was used to validate the models. The simulation results demonstrated that the ANFIS model having achieved MAPE of 5.34% outperformed the ARMAX model. The ANFIS could be a valuable tool for forecasting the global solar radiation.

Development of Regional Power Sector Coal Fuel Costs (Prices) for the Short-Term Energy Outlook (STEO) Model

EIA Publications

2017-01-01

The U.S. Energy Information Administration's Short-Term Energy Outlook (STEO) produces monthly projections of energy supply, demand, trade, and prices over a 13-24 month period. Every January, the forecast horizon is extended through December of the following year. The STEO model is an integrated system of econometric regression equations and identities that link data on the various components of the U.S. energy industry together in order to develop consistent forecasts. The regression equations are estimated and the STEO model is solved using the EViews 9.5 econometric software package from IHS Global Inc. The model consists of various modules specific to each energy resource. All modules provide projections for the United States, and some modules provide more detailed forecasts for different regions of the country.

Evaluation of annual, global seismicity forecasts, including ensemble models

NASA Astrophysics Data System (ADS)

Taroni, Matteo; Zechar, Jeremy; Marzocchi, Warner

2013-04-01

In 2009, the Collaboratory for the Study of the Earthquake Predictability (CSEP) initiated a prototype global earthquake forecast experiment. Three models participated in this experiment for 2009, 2010 and 2011—each model forecast the number of earthquakes above magnitude 6 in 1x1 degree cells that span the globe. Here we use likelihood-based metrics to evaluate the consistency of the forecasts with the observed seismicity. We compare model performance with statistical tests and a new method based on the peer-to-peer gambling score. The results of the comparisons are used to build ensemble models that are a weighted combination of the individual models. Notably, in these experiments the ensemble model always performs significantly better than the single best-performing model. Our results indicate the following: i) time-varying forecasts, if not updated after each major shock, may not provide significant advantages with respect to time-invariant models in 1-year forecast experiments; ii) the spatial distribution seems to be the most important feature to characterize the different forecasting performances of the models; iii) the interpretation of consistency tests may be misleading because some good models may be rejected while trivial models may pass consistency tests; iv) a proper ensemble modeling seems to be a valuable procedure to get the best performing model for practical purposes.

A robust method to forecast volcanic ash clouds

USGS Publications Warehouse

Denlinger, Roger P.; Pavolonis, Mike; Sieglaff, Justin

2012-01-01

Ash clouds emanating from volcanic eruption columns often form trails of ash extending thousands of kilometers through the Earth's atmosphere, disrupting air traffic and posing a significant hazard to air travel. To mitigate such hazards, the community charged with reducing flight risk must accurately assess risk of ash ingestion for any flight path and provide robust forecasts of volcanic ash dispersal. In response to this need, a number of different transport models have been developed for this purpose and applied to recent eruptions, providing a means to assess uncertainty in forecasts. Here we provide a framework for optimal forecasts and their uncertainties given any model and any observational data. This involves random sampling of the probability distributions of input (source) parameters to a transport model and iteratively running the model with different inputs, each time assessing the predictions that the model makes about ash dispersal by direct comparison with satellite data. The results of these comparisons are embodied in a likelihood function whose maximum corresponds to the minimum misfit between model output and observations. Bayes theorem is then used to determine a normalized posterior probability distribution and from that a forecast of future uncertainty in ash dispersal. The nature of ash clouds in heterogeneous wind fields creates a strong maximum likelihood estimate in which most of the probability is localized to narrow ranges of model source parameters. This property is used here to accelerate probability assessment, producing a method to rapidly generate a prediction of future ash concentrations and their distribution based upon assimilation of satellite data as well as model and data uncertainties. Applying this method to the recent eruption of Eyjafjallajökull in Iceland, we show that the 3 and 6 h forecasts of ash cloud location probability encompassed the location of observed satellite-determined ash cloud loads, providing an

22 CFR 518.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award... analysis may be accomplished in various ways, including the comparison of price quotations submitted...

49 CFR 19.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-10-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award... analysis may be accomplished in various ways, including the comparison of price quotations submitted...

49 CFR 19.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-10-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award... analysis may be accomplished in various ways, including the comparison of price quotations submitted...

22 CFR 518.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award... analysis may be accomplished in various ways, including the comparison of price quotations submitted...

49 CFR 19.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-10-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award... analysis may be accomplished in various ways, including the comparison of price quotations submitted...

22 CFR 518.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award... analysis may be accomplished in various ways, including the comparison of price quotations submitted...

22 CFR 518.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award... analysis may be accomplished in various ways, including the comparison of price quotations submitted...

22 CFR 518.45 - Cost and price analysis.

Code of Federal Regulations, 2010 CFR

2010-04-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award... analysis may be accomplished in various ways, including the comparison of price quotations submitted...

49 CFR 19.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-10-01

... AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, AND OTHER NON-PROFIT ORGANIZATIONS Post-Award... analysis may be accomplished in various ways, including the comparison of price quotations submitted...

Analysis of a 10% Renewable Portfolio Standard, Addendum

EIA Publications

2003-01-01

On May 8, 2003, Senator Jeff Bingaman, the Ranking Minority Member of the Senate Committee on Energy and Natural Resources, requested an analysis of a nationwide Renewable Portfolio Standard (RPS) program proposed to be amended to energy legislation currently pending before the U.S. Senate. With his request Sen. Bingaman provided specific information on the program to be analyzed. This analysis was prepared in response to his request and projects the impact of the proposed program on energy supply, demand, prices, and emissions. The analysis is based on the Annual Energy Outlook 2003 (AEO2003) projections of energy supply, demand, and prices through 2025, as updated in May 2003.

Analysis of a 10% Renewable Portfolio Standard

EIA Publications

2003-01-01

On May 8, 2003, Senator Jeff Bingaman, the Ranking Minority Member of the Senate Committee on Energy and Natural Resources, requested an analysis of a nationwide Renewable Portfolio Standard (RPS) program proposed to be amended to energy legislation currently pending before the U.S. Senate. With his request Sen. Bingaman provided specific information on the program to be analyzed. This analysis was prepared in response to his request and projects the impact of the proposed program on energy supply, demand, prices, and emissions. The analysis is based on the Annual Energy Outlook 2003 (AEO2003) projections of energy supply, demand, and prices through 2025, as updated in May 2003.

A Comparison of Model Short-Range Forecasts and the ARM Microbase Data Fourth Quarter ARM Science Metric

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hnilo, J.

2006-09-19

For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the “Microbase” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averagedmore » to 3hourly data for direct comparison to our model output.« less

Comparison of Filtering Methods for the Modeling and Retrospective Forecasting of Influenza Epidemics

PubMed Central

Yang, Wan; Karspeck, Alicia; Shaman, Jeffrey

2014-01-01

A variety of filtering methods enable the recursive estimation of system state variables and inference of model parameters. These methods have found application in a range of disciplines and settings, including engineering design and forecasting, and, over the last two decades, have been applied to infectious disease epidemiology. For any system of interest, the ideal filter depends on the nonlinearity and complexity of the model to which it is applied, the quality and abundance of observations being entrained, and the ultimate application (e.g. forecast, parameter estimation, etc.). Here, we compare the performance of six state-of-the-art filter methods when used to model and forecast influenza activity. Three particle filters—a basic particle filter (PF) with resampling and regularization, maximum likelihood estimation via iterated filtering (MIF), and particle Markov chain Monte Carlo (pMCMC)—and three ensemble filters—the ensemble Kalman filter (EnKF), the ensemble adjustment Kalman filter (EAKF), and the rank histogram filter (RHF)—were used in conjunction with a humidity-forced susceptible-infectious-recovered-susceptible (SIRS) model and weekly estimates of influenza incidence. The modeling frameworks, first validated with synthetic influenza epidemic data, were then applied to fit and retrospectively forecast the historical incidence time series of seven influenza epidemics during 2003–2012, for 115 cities in the United States. Results suggest that when using the SIRS model the ensemble filters and the basic PF are more capable of faithfully recreating historical influenza incidence time series, while the MIF and pMCMC do not perform as well for multimodal outbreaks. For forecast of the week with the highest influenza activity, the accuracies of the six model-filter frameworks are comparable; the three particle filters perform slightly better predicting peaks 1–5 weeks in the future; the ensemble filters are more accurate predicting peaks in the

The impact of alternative pricing methods for drugs in California Workers’ Compensation System: Fee-schedule pricing

PubMed Central

Wilson, Leslie; Turkistani, Fatema A.; Huang, Wei; Tran, Dang M.; Lin, Tracy Kuo

2018-01-01

Introduction California’s Workers’ Compensation System (CAWCS) Department of Industrial Relations questioned the adequacy of the current Medi-Cal fee-schedule pricing and requested analysis of alternatives that maximize price availability and maintain budget neutrality. Objectives To compare CAWCS pharmacy-dispensed (PD) drug prices under alternative fee schedules, and identify combinations of alternative benchmarks that have prices available for the largest percentage of PD drugs and that best reach budget neutrality. Methods Claims transaction-level data (2011–2013) from CAWCS were used to estimate total annual PD pharmaceutical payments. Medi-Cal pricing data was from the Workman’s Compensation Insurance System (WCIS). Average Wholesale Prices (AWP), Wholesale Acquisition Costs (WAC), Direct Prices (DP), Federal Upper Limit (FUL) prices, and National Average Drug Acquisition Costs (NADAC) were from Medi-Span. We matched National Drug Codes (NDCs), pricing dates, and drug quantity for comparisons. We report pharmacy-dispensed (PD) claims frequency, reimbursement matching rate, and paid costs by CAWCS as the reference price against all alternative price benchmarks. Results Of 12,529,977 CAWCS claims for pharmaceutical products 11.6% (1,462,814) were for PD drugs. Prescription drug cost for CAWCS was over $152M; $63.9M, $47.9M, and $40.6M in 2011–2013. Ninety seven percent of these CAWCS PD claims had a Medi-Cal price. Alternative mechanisms provided a price for fewer claims; NADAC 94.23%, AWP 90.94%, FUL 73.11%, WAC 66.98%, and DP 14.33%. Among CAWCS drugs with no Medi-Cal price in PD claims, AWP, WAC, NADAC, DP, and FUL provided prices for 96.7%, 63.14%, 24.82%, 20.83%, and 15.08% of claims. Overall CAWCS paid 100.52% of Medi-Cal, 60% of AWP, 97% of WAC, 309.53% of FUL, 103.83% of DP, and 136.27% of NADAC. Conclusions CAWCS current Medi-Cal fee-schedule price list for PD drugs is more complete than all alternative fee-schedules. However, all

Ocean observing systems support operational forecasts for the timing of Maine's lobster fishery

NASA Astrophysics Data System (ADS)

Mills, K.; Hernandez, C.; Pershing, A. J.

2016-02-01

American lobster supports one of the most valuable fisheries in the United States, with a landed value in 2013 exceeding $460M. Although US lobstermen are free to fish throughout the year, the New England climate, lobster biology and fleet dynamics lead to a strong annual cycle with catch rates rising rapidly in early summer and landings peaking in late summer. When this annual cycle is disrupted, it can impact the supply and ultimately the price of lobsters. During the record warm conditions in 2012, the rise in catch rates occurred three weeks ahead of normal. Combined with higher than normal landings from the spring Canadian fishery, the early and high volume landings in 2012 led to a collapse in price that severely stressed the U. S. fishery, especially in Maine where over 85% of the landings occur. Based on this experience, we have been developing seasonal forecasts of the phenology of Maine lobster landings. Using temperatures at 50m from four NERACOOS buoys in the Gulf of Maine, we can reliably forecast the date when the Maine lobster fishery will `turn on' for the year, with prediction accuracy peaking in April. The high-landings period normally starts in July, and the 2-3 month lead-time provides some advance warning to dealers and processors of when their capacity needs to be ready and to fishermen of potential supply chain and market impacts such as we observed in 2012. We are currently working towards finer-scale regional forecasts along the Maine coast that may include other features that will provide information to help the lobster industry adapt to the rapid changes that are underway in the Gulf of Maine.

15 CFR 14.45 - Cost and price analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

... REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NON-PROFIT, AND... every procurement action. Price analysis may be accomplished in various ways, including the comparison...

15 CFR 14.45 - Cost and price analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NON-PROFIT, AND... every procurement action. Price analysis may be accomplished in various ways, including the comparison...

15 CFR 14.45 - Cost and price analysis.

Code of Federal Regulations, 2011 CFR

2011-01-01

... REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NON-PROFIT, AND... every procurement action. Price analysis may be accomplished in various ways, including the comparison...

15 CFR 14.45 - Cost and price analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... REQUIREMENTS FOR GRANTS AND AGREEMENTS WITH INSTITUTIONS OF HIGHER EDUCATION, HOSPITALS, OTHER NON-PROFIT, AND... every procurement action. Price analysis may be accomplished in various ways, including the comparison...

A Structured and Unstructured grid Relocatable ocean platform for Forecasting (SURF)

NASA Astrophysics Data System (ADS)

Trotta, Francesco; Fenu, Elisa; Pinardi, Nadia; Bruciaferri, Diego; Giacomelli, Luca; Federico, Ivan; Coppini, Giovanni

2016-11-01

We present a numerical platform named Structured and Unstructured grid Relocatable ocean platform for Forecasting (SURF). The platform is developed for short-time forecasts and is designed to be embedded in any region of the large-scale Mediterranean Forecasting System (MFS) via downscaling. We employ CTD data collected during a campaign around the Elba island to calibrate and validate SURF. The model requires an initial spin up period of a few days in order to adapt the initial interpolated fields and the subsequent solutions to the higher-resolution nested grids adopted by SURF. Through a comparison with the CTD data, we quantify the improvement obtained by SURF model compared to the coarse-resolution MFS model.

Development of an evolutionary fuzzy expert system for estimating future behavior of stock price

NASA Astrophysics Data System (ADS)

Mehmanpazir, Farhad; Asadi, Shahrokh

2017-03-01

The stock market has always been an attractive area for researchers since no method has been found yet to predict the stock price behavior precisely. Due to its high rate of uncertainty and volatility, it carries a higher risk than any other investment area, thus the stock price behavior is difficult to simulation. This paper presents a "data mining-based evolutionary fuzzy expert system" (DEFES) approach to estimate the behavior of stock price. This tool is developed in seven-stage architecture. Data mining is used in three stages to reduce the complexity of the whole data space. The first stage, noise filtering, is used to make our raw data clean and smooth. Variable selection is second stage; we use stepwise regression analysis to choose the key variables been considered in the model. In the third stage, K-means is used to divide the data into sub-populations to decrease the effects of noise and rebate complexity of the patterns. At next stage, extraction of Mamdani type fuzzy rule-based system will be carried out for each cluster by means of genetic algorithm and evolutionary strategy. In the fifth stage, we use binary genetic algorithm to rule filtering to remove the redundant rules in order to solve over learning phenomenon. In the sixth stage, we utilize the genetic tuning process to slightly adjust the shape of the membership functions. Last stage is the testing performance of tool and adjusts parameters. This is the first study on using an approximate fuzzy rule base system and evolutionary strategy with the ability of extracting the whole knowledge base of fuzzy expert system for stock price forecasting problems. The superiority and applicability of DEFES are shown for International Business Machines Corporation and compared the outcome with the results of the other methods. Results with MAPE metric and Wilcoxon signed ranks test indicate that DEFES provides more accuracy and outperforms all previous methods, so it can be considered as a superior tool for

An island apart? Risks and prices in the Australian cryptomarket drug trade.

PubMed

Cunliffe, Jack; Martin, James; Décary-Hétu, David; Aldridge, Judith

2017-12-01

Australia has a reputation as an anomaly with regard to cryptomarket drug trading, with seemingly disproportionately high levels of activity given its relatively small size, high prices and anecdotal accounts of it being a destination where many foreign-based vendors will not sell. This paper aims to investigate these claims from a risk and prices perspective. By analysing data for over 60,000 drug products available for purchase from eight cryptomarkets in January 2016 this work builds a descriptive picture of the Australian online market in comparison to the rest of the world, before moving onto analyse the prices of drugs available to Australian consumers, both online and though conventional drug supply routes. Results show that the Australian online illicit drugs market is of considerable size, internally isolated and with methamphetamine sales being particularly large by comparison to other countries. Australian cryptomarket vendors sell drugs at significantly higher prices than those listed by their foreign counterparts. Online prices are however broadly comparable to street prices, with the exception of methamphetamine where prices appear to be much lower online. These findings indicate that the perceived stringency of Australian border protection inadvertently increases the competitiveness and local market share of domestic cryptomarket vendors via a consumer side 'risk tariff', challenging the traditionally vendor-oriented drugs risk and prices framework. Copyright © 2017 Elsevier B.V. All rights reserved.

A Comparison Study of Return Ratio-Based Academic Enrollment Forecasting Models. Professional File. Article 129, Spring 2013

ERIC Educational Resources Information Center

Zan, Xinxing Anna; Yoon, Sang Won; Khasawneh, Mohammad; Srihari, Krishnaswami

2013-01-01

In an effort to develop a low-cost and user-friendly forecasting model to minimize forecasting error, we have applied average and exponentially weighted return ratios to project undergraduate student enrollment. We tested the proposed forecasting models with different sets of historical enrollment data, such as university-, school-, and…

Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

NASA Technical Reports Server (NTRS)

Watson, Leela R.

2007-01-01

This report describes the work done by the Applied Meteorology Unit (AMU) in assessing the success of different model configurations in predicting warm season convection over East-Central Florida. The Weather Research and Forecasting Environmental Modeling System (WRF EMS) software allows users to choose among two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model - the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Besides model core and initialization options, the WRF model can be run with one- or two-way nesting. Having a series of initialization options and WRF cores, as well as many options within each core, creates challenges for local forecasters, such as determining which configuration options are best to address specific forecast concerns. This project assessed three different model intializations available to determine which configuration best predicts warm season convective initiation in East-Central Florida. The project also examined the use of one- and two-way nesting in predicting warm season convection.

Price and utilisation differences for statins between four countries.

PubMed

Thai, Loc Phuoc; Vitry, Agnes Isabelle; Moss, John Robert

2018-02-01

Australia, England, France and New Zealand use different policies to regulate their medicines market, which can impact on utilisation and price. To compare the prices and utilisation of statins in Australia, England, France and New Zealand from 2011 to 2013. Utilisation of statins in the four countries was compared using Defined Daily Doses (DDD) per 1000 inhabitants per year. Pairwise Laspeyres and Paasche index comparisons were conducted comparing the price and utilisation of statins. The results showed that the price of statins in New Zealand was the cheapest. The price of statins in Australia was most expensive in 2011 and 2012 but France was more expensive in 2013. There were large differences between the Laspeyres index and Paasche index when comparing the price and utilisation of England with Australia and France. The policies that regulate the New Zealand and England medicines markets were more effective in reducing the price of expensive statins. The relative utilisation of cheaper statins was greatest in England and had a large effect on the differences between the two index results. The pricing policies in Australia have been only partly effective in reducing the price of statins compared to other countries.

A simplified real time method to forecast semi-enclosed basins storm surge

NASA Astrophysics Data System (ADS)

Pasquali, D.; Di Risio, M.; De Girolamo, P.

2015-11-01

Semi-enclosed basins are often prone to storm surge events. Indeed, their meteorological exposition, the presence of large continental shelf and their shape can lead to strong sea level set-up. A real time system aimed at forecasting storm surge may be of great help to protect human activities (i.e. to forecast flooding due to storm surge events), to manage ports and to safeguard coasts safety. This paper aims at illustrating a simple method able to forecast storm surge events in semi-enclosed basins in real time. The method is based on a mixed approach in which the results obtained by means of a simplified physics based model with low computational costs are corrected by means of statistical techniques. The proposed method is applied to a point of interest located in the Northern part of the Adriatic Sea. The comparison of forecasted levels against observed values shows the satisfactory reliability of the forecasts.

Added value of dynamical downscaling of winter seasonal forecasts over North America

NASA Astrophysics Data System (ADS)

Tefera Diro, Gulilat; Sushama, Laxmi

2017-04-01

Skillful seasonal forecasts have enormous potential benefits for socio-economic sectors that are sensitive to weather and climate conditions, as the early warning routines could reduce the vulnerability of such sectors. In this study, individual ensemble members of the ECMWF global ensemble seasonal forecasts are dynamically downscaled to produce ensemble of regional seasonal forecasts over North America using the fifth generation Canadian Regional Climate Model (CRCM5). CRCM5 forecasts are initialized on November 1st of each year and are integrated for four months for the 1991-2001 period at 0.22 degree resolution to produce a one-month lead-time forecast. The initial conditions for atmospheric variables are obtained from ERA-Interim reanalysis, whereas the initial conditions for land surface are obtained from a separate ERA-interim driven CRCM5 simulation with spectral nudging applied to the interior domain. The global and regional ensemble forecasts were then verified to investigate the skill and economic benefits of dynamical downscaling. Results indicate that both the global and regional climate models produce skillful precipitation forecast over the southern Great Plains and eastern coasts of the U.S and skillful temperature forecasts over the northern U.S. and most of Canada. In comparison to ECMWF forecasts, CRCM5 forecasts improved the temperature forecast skill over most part of the domain, but the improvements for precipitation is limited to regions with complex topography, where it improves the frequency of intense daily precipitation. CRCM5 forecast also yields a better economic value compared to ECMWF precipitation forecasts, for users whose cost to loss ratio is smaller than 0.5.

Forecasting Skill

DTIC Science & Technology

1981-01-01

for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

7 CFR 1030.50 - Class prices, component prices, and advanced pricing factors.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1030.50 Section 1030.50 Agriculture Regulations of the Department of Agriculture (Continued... prices, and advanced pricing factors. See § 1000.50. ...

7 CFR 1124.50 - Class prices, component prices, and advanced pricing factors.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1124.50 Section 1124.50 Agriculture Regulations of the Department of Agriculture (Continued... prices, and advanced pricing factors. See § 1000.50. ...

Pharmaceutical policies: effects of reference pricing, other pricing, and purchasing policies.

PubMed

Acosta, Angela; Ciapponi, Agustín; Aaserud, Morten; Vietto, Valeria; Austvoll-Dahlgren, Astrid; Kösters, Jan Peter; Vacca, Claudia; Machado, Manuel; Diaz Ayala, Diana Hazbeydy; Oxman, Andrew D

2014-10-16

, healthcare utilisation and health outcomes or costs (expenditures); the study had to be a randomised trial, non-randomised trial, interrupted time series (ITS), repeated measures (RM) study or a controlled before-after study of a pharmaceutical pricing or purchasing policy for a large jurisdiction or system of care. Two review authors independently extracted data and assessed the risk of bias. Results were summarised in tables. There were too few comparisons with similar outcomes across studies to allow for meta-analysis or meaningful exploration of heterogeneity. We included 18 studies (seven identified in the update): 17 of reference pricing, one of which also assessed maximum prices, and one of index pricing. None of the studies were trials. All included studies used ITS or RM analyses. The quality of the evidence was low or very low for all outcomes. Three reference pricing studies reported cumulative drug expenditures at one year after the transition period. Two studies reported the median relative insurer's cumulative expenditures, on both reference drugs and cost share drugs, of -18%, ranging from -36% to 3%. The third study reported relative insurer's cumulative expenditures on total market of -1.5%. Four reference pricing studies reported median relative insurer's expenditures on both reference drugs and cost share drugs of -10%, ranging from -53% to 4% at one year after the transition period. Four reference pricing studies reported a median relative change of 15% in reference drugs prescriptions at one year (range -14% to 166%). Three reference pricing studies reported a median relative change of -39% in cost share drugs prescriptions at one year (range -87% to -17%). One study of index pricing reported a relative change of 55% (95% CI 11% to 98%) in the use of generic drugs and -43% relative change (95% CI -67% to -18%) in brand drugs at six months after the transition period. The same study reported a price change of -5.3% and -1.1% for generic and brand drugs

Comparison between intensity- duration thresholds and cumulative rainfall thresholds for the forecasting of landslide

NASA Astrophysics Data System (ADS)

Lagomarsino, Daniela; Rosi, Ascanio; Rossi, Guglielmo; Segoni, Samuele; Catani, Filippo

2014-05-01

This work makes a quantitative comparison between the results of landslide forecasting obtained using two different rainfall threshold models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds in an area of northern Tuscany of 116 km2. The first methodology identifies rainfall intensity-duration thresholds by means a software called MaCumBA (Massive CUMulative Brisk Analyzer) that analyzes rain-gauge records, extracts the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram, and identifies thresholds that define the lower bounds of the I-D values. A back analysis using data from past events can be used to identify the threshold conditions associated with the least amount of false alarms. The second method (SIGMA) is based on the hypothesis that anomalous or extreme values of rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations in the proposed methodology. The definition of intensity-duration rainfall thresholds requires the combined use of rainfall measurements and an inventory of dated landslides, whereas SIGMA model can be implemented using only rainfall data. These two methodologies were applied in an area of 116 km2 where a database of 1200 landslides was available for the period 2000-2012. The results obtained are compared and discussed. Although several examples of visual comparisons between different intensity-duration rainfall thresholds are reported in the international literature, a quantitative comparison between thresholds obtained in the same area using different techniques and approaches is a relatively undebated research topic.

A Comparison of Pricing Strategies for Bibliographical Databases on CDROM and Equivalent Printed Products.

ERIC Educational Resources Information Center

Rowley, Jennifer; Butcher, David

1994-01-01

Considers comparative prices for bibliographic data on CD-ROM and in print. Topics addressed include differences in the nature of bibliographic data in the two media, the relative complexities of pricing structure, varying policies on network pricing, and standardization of the licensing arrangement. (KRN)

Evaluating the Impacts of Real-Time Pricing on the Cost and Value of Wind Generation

DOE PAGES

Siohansi, Ramteen

2010-05-01

One of the costs associated with integrating wind generation into a power system is the cost of redispatching the system in real-time due to day-ahead wind resource forecast errors. One possible way of reducing these redispatch costs is to introduce demand response in the form of real-time pricing (RTP), which could allow electricity demand to respond to actual real-time wind resource availability using price signals. A day-ahead unit commitment model with day-ahead wind forecasts and a real-time dispatch model with actual wind resource availability is used to estimate system operations in a high wind penetration scenario. System operations are comparedmore » to a perfect foresight benchmark, in which actual wind resource availability is known day-ahead. The results show that wind integration costs with fixed demands can be high, both due to real-time redispatch costs and lost load. It is demonstrated that introducing RTP can reduce redispatch costs and eliminate loss of load events. Finally, social surplus with wind generation and RTP is compared to a system with neither and the results demonstrate that introducing wind and RTP into a market can result in superadditive surplus gains.« less

Automated turbulence forecasts for aviation hazards

NASA Astrophysics Data System (ADS)

Sharman, R.; Frehlich, R.; Vandenberghe, F.

2010-09-01

An operational turbulence forecast system for commercial and aviation use is described that is based on an ensemble of turbulence diagnostics derived from standard NWP model outputs. In the U. S. this forecast product is named GTG (Graphical Turbulence Guidance) and has been described in detail in Sharman et al., WAF 2006. Since turbulence has many sources in the atmosphere, the ensemble approach of combining diagnostics has been shown to provide greater statistical accuracy than the use of a single diagnostic, or of a subgrid tke parameterization. GTG is sponsored by the FAA, and has undergone rigorous accuracy, safety, and usability evaluations. The GTG product is now hosted on NOAA's Aviation Data Service (ADDS), web site (http://aviationweather.gov/), for access by pilots, air traffic controllers, and dispatchers. During this talk the various turbulence diagnostics, their statistical properties, and their relative performance (based on comparisons to observations) will be presented. Importantly, the model output is ɛ1/3 (where ɛ is the eddy dissipation rate), so is aircraft independent. The diagnostics are individually and collectively calibrated so that their PDFs satisfy the expected log normal distribution of ɛ^1/3. Some of the diagnostics try to take into account the role of gravity waves and inertia-gravity waves in the turbulence generation process. Although the current GTG product is based on the RUC forecast model running over the CONUS, it is transitioning to a WRF based product, and in fact WRF-based versions are currently running operationally over Taiwan and has also been implemented for use by the French Navy in climatological studies. Yet another version has been developed which uses GFS model output to provide global turbulence forecasts. Thus the forecast product is available as a postprocessing program for WRF or other model output and provides 3D maps of turbulence likelihood of any region where NWP model data is available. Although the

Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

NASA Astrophysics Data System (ADS)

Shafiee-Jood, M.; Cai, X.

2017-12-01

Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

Understanding Farmers’ Forecast Use from Their Beliefs, Values, Social Norms, and Perceived Obstacles

NASA Astrophysics Data System (ADS)

Hu, Qi; Pytlik Zillig, Lisa M.; Lynne, Gary D.; Tomkins, Alan J.; Waltman, William J.; Hayes, Michael J.; Hubbard, Kenneth G.; Artikov, Ikrom; Hoffman, Stacey J.; Wilhite, Donald A.

2006-09-01

Although the accuracy of weather and climate forecasts is continuously improving and new information retrieved from climate data is adding to the understanding of climate variation, use of the forecasts and climate information by farmers in farming decisions has changed little. This lack of change may result from knowledge barriers and psychological, social, and economic factors that undermine farmer motivation to use forecasts and climate information. According to the theory of planned behavior (TPB), the motivation to use forecasts may arise from personal attitudes, social norms, and perceived control or ability to use forecasts in specific decisions. These attributes are examined using data from a survey designed around the TPB and conducted among farming communities in the region of eastern Nebraska and the western U.S. Corn Belt. There were three major findings: 1) the utility and value of the forecasts for farming decisions as perceived by farmers are, on average, around 3.0 on a 0 7 scale, indicating much room to improve attitudes toward the forecast value. 2) The use of forecasts by farmers to influence decisions is likely affected by several social groups that can provide “expert viewpoints” on forecast use. 3) A major obstacle, next to forecast accuracy, is the perceived identity and reliability of the forecast makers. Given the rapidly increasing number of forecasts in this growing service business, the ambiguous identity of forecast providers may have left farmers confused and may have prevented them from developing both trust in forecasts and skills to use them. These findings shed light on productive avenues for increasing the influence of forecasts, which may lead to greater farming productivity. In addition, this study establishes a set of reference points that can be used for comparisons with future studies to quantify changes in forecast use and influence.

Interactive Forecasting with the National Weather Service River Forecast System

NASA Technical Reports Server (NTRS)

Smith, George F.; Page, Donna

1993-01-01

The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

Hydro-meteorological evaluation of downscaled global ensemble rainfall forecasts

NASA Astrophysics Data System (ADS)

Gaborit, Étienne; Anctil, François; Fortin, Vincent; Pelletier, Geneviève

2013-04-01

Ensemble rainfall forecasts are of high interest for decision making, as they provide an explicit and dynamic assessment of the uncertainty in the forecast (Ruiz et al. 2009). However, for hydrological forecasting, their low resolution currently limits their use to large watersheds (Maraun et al. 2010). In order to bridge this gap, various implementations of the statistic-stochastic multi-fractal downscaling technique presented by Perica and Foufoula-Georgiou (1996) were compared, bringing Environment Canada's global ensemble rainfall forecasts from a 100 by 70-km resolution down to 6 by 4-km, while increasing each pixel's rainfall variance and preserving its original mean. For comparison purposes, simpler methods were also implemented such as the bi-linear interpolation, which disaggregates global forecasts without modifying their variance. The downscaled meteorological products were evaluated using different scores and diagrams, from both a meteorological and a hydrological view points. The meteorological evaluation was conducted comparing the forecasted rainfall depths against nine days of observed values taken from Québec City rain gauge database. These 9 days present strong precipitation events occurring during the summer of 2009. For the hydrologic evaluation, the hydrological models SWMM5 and (a modified version of) GR4J were implemented on a small 6 km2 urban catchment located in the Québec City region. Ensemble hydrologic forecasts with a time step of 3 hours were then performed over a 3-months period of the summer of 2010 using the original and downscaled ensemble rainfall forecasts. The most important conclusions of this work are that the overall quality of the forecasts was preserved during the disaggregation procedure and that the disaggregated products using this variance-enhancing method were of similar quality than bi-linear interpolation products. However, variance and dispersion of the different members were, of course, much improved for the