Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data.

PubMed

Xu, Lizhen; Paterson, Andrew D; Turpin, Williams; Xu, Wei

2015-01-01

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects.

Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression.

PubMed

Lao, Yunteng; Wu, Yao-Jan; Corey, Jonathan; Wang, Yinhai

2011-01-01

Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ(1), λ(2) and λ(3)). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs. Published by Elsevier Ltd.

Zero-inflated Poisson model based likelihood ratio test for drug safety signal detection.

PubMed

Huang, Lan; Zheng, Dan; Zalkikar, Jyoti; Tiwari, Ram

2017-02-01

In recent decades, numerous methods have been developed for data mining of large drug safety databases, such as Food and Drug Administration's (FDA's) Adverse Event Reporting System, where data matrices are formed by drugs such as columns and adverse events as rows. Often, a large number of cells in these data matrices have zero cell counts and some of them are "true zeros" indicating that the drug-adverse event pairs cannot occur, and these zero counts are distinguished from the other zero counts that are modeled zero counts and simply indicate that the drug-adverse event pairs have not occurred yet or have not been reported yet. In this paper, a zero-inflated Poisson model based likelihood ratio test method is proposed to identify drug-adverse event pairs that have disproportionately high reporting rates, which are also called signals. The maximum likelihood estimates of the model parameters of zero-inflated Poisson model based likelihood ratio test are obtained using the expectation and maximization algorithm. The zero-inflated Poisson model based likelihood ratio test is also modified to handle the stratified analyses for binary and categorical covariates (e.g. gender and age) in the data. The proposed zero-inflated Poisson model based likelihood ratio test method is shown to asymptotically control the type I error and false discovery rate, and its finite sample performance for signal detection is evaluated through a simulation study. The simulation results show that the zero-inflated Poisson model based likelihood ratio test method performs similar to Poisson model based likelihood ratio test method when the estimated percentage of true zeros in the database is small. Both the zero-inflated Poisson model based likelihood ratio test and likelihood ratio test methods are applied to six selected drugs, from the 2006 to 2011 Adverse Event Reporting System database, with varying percentages of observed zero-count cells.

Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections.

PubMed

Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan

2014-09-01

Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.

Functional linear models for zero-inflated count data with application to modeling hospitalizations in patients on dialysis.

PubMed

Sentürk, Damla; Dalrymple, Lorien S; Nguyen, Danh V

2014-11-30

We propose functional linear models for zero-inflated count data with a focus on the functional hurdle and functional zero-inflated Poisson (ZIP) models. Although the hurdle model assumes the counts come from a mixture of a degenerate distribution at zero and a zero-truncated Poisson distribution, the ZIP model considers a mixture of a degenerate distribution at zero and a standard Poisson distribution. We extend the generalized functional linear model framework with a functional predictor and multiple cross-sectional predictors to model counts generated by a mixture distribution. We propose an estimation procedure for functional hurdle and ZIP models, called penalized reconstruction, geared towards error-prone and sparsely observed longitudinal functional predictors. The approach relies on dimension reduction and pooling of information across subjects involving basis expansions and penalized maximum likelihood techniques. The developed functional hurdle model is applied to modeling hospitalizations within the first 2 years from initiation of dialysis, with a high percentage of zeros, in the Comprehensive Dialysis Study participants. Hospitalization counts are modeled as a function of sparse longitudinal measurements of serum albumin concentrations, patient demographics, and comorbidities. Simulation studies are used to study finite sample properties of the proposed method and include comparisons with an adaptation of standard principal components regression. Copyright © 2014 John Wiley & Sons, Ltd.

Modeling health survey data with excessive zero and K responses.

PubMed

Lin, Ting Hsiang; Tsai, Min-Hsiao

2013-04-30

Zero-inflated Poisson regression is a popular tool used to analyze data with excessive zeros. Although much work has already been performed to fit zero-inflated data, most models heavily depend on special features of the individual data. To be specific, this means that there is a sizable group of respondents who endorse the same answers making the data have peaks. In this paper, we propose a new model with the flexibility to model excessive counts other than zero, and the model is a mixture of multinomial logistic and Poisson regression, in which the multinomial logistic component models the occurrence of excessive counts, including zeros, K (where K is a positive integer) and all other values. The Poisson regression component models the counts that are assumed to follow a Poisson distribution. Two examples are provided to illustrate our models when the data have counts containing many ones and sixes. As a result, the zero-inflated and K-inflated models exhibit a better fit than the zero-inflated Poisson and standard Poisson regressions. Copyright © 2012 John Wiley & Sons, Ltd.

EM Adaptive LASSO—A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes

PubMed Central

Mallick, Himel; Tiwari, Hemant K.

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice

EM Adaptive LASSO-A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes.

PubMed

Mallick, Himel; Tiwari, Hemant K

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice.

Marginalized multilevel hurdle and zero-inflated models for overdispersed and correlated count data with excess zeros.

PubMed

Kassahun, Wondwosen; Neyens, Thomas; Molenberghs, Geert; Faes, Christel; Verbeke, Geert

2014-11-10

Count data are collected repeatedly over time in many applications, such as biology, epidemiology, and public health. Such data are often characterized by the following three features. First, correlation due to the repeated measures is usually accounted for using subject-specific random effects, which are assumed to be normally distributed. Second, the sample variance may exceed the mean, and hence, the theoretical mean-variance relationship is violated, leading to overdispersion. This is usually allowed for based on a hierarchical approach, combining a Poisson model with gamma distributed random effects. Third, an excess of zeros beyond what standard count distributions can predict is often handled by either the hurdle or the zero-inflated model. A zero-inflated model assumes two processes as sources of zeros and combines a count distribution with a discrete point mass as a mixture, while the hurdle model separately handles zero observations and positive counts, where then a truncated-at-zero count distribution is used for the non-zero state. In practice, however, all these three features can appear simultaneously. Hence, a modeling framework that incorporates all three is necessary, and this presents challenges for the data analysis. Such models, when conditionally specified, will naturally have a subject-specific interpretation. However, adopting their purposefully modified marginalized versions leads to a direct marginal or population-averaged interpretation for parameter estimates of covariate effects, which is the primary interest in many applications. In this paper, we present a marginalized hurdle model and a marginalized zero-inflated model for correlated and overdispersed count data with excess zero observations and then illustrate these further with two case studies. The first dataset focuses on the Anopheles mosquito density around a hydroelectric dam, while adolescents' involvement in work, to earn money and support their families or themselves, is

Evaluation of the Use of Zero-Augmented Regression Techniques to Model Incidence of Campylobacter Infections in FoodNet.

PubMed

Tremblay, Marlène; Crim, Stacy M; Cole, Dana J; Hoekstra, Robert M; Henao, Olga L; Döpfer, Dörte

2017-10-01

The Foodborne Diseases Active Surveillance Network (FoodNet) is currently using a negative binomial (NB) regression model to estimate temporal changes in the incidence of Campylobacter infection. FoodNet active surveillance in 483 counties collected data on 40,212 Campylobacter cases between years 2004 and 2011. We explored models that disaggregated these data to allow us to account for demographic, geographic, and seasonal factors when examining changes in incidence of Campylobacter infection. We hypothesized that modeling structural zeros and including demographic variables would increase the fit of FoodNet's Campylobacter incidence regression models. Five different models were compared: NB without demographic covariates, NB with demographic covariates, hurdle NB with covariates in the count component only, hurdle NB with covariates in both zero and count components, and zero-inflated NB with covariates in the count component only. Of the models evaluated, the nonzero-augmented NB model with demographic variables provided the best fit. Results suggest that even though zero inflation was not present at this level, individualizing the level of aggregation and using different model structures and predictors per site might be required to correctly distinguish between structural and observational zeros and account for risk factors that vary geographically.

Zero-inflated spatio-temporal models for disease mapping.

PubMed

Torabi, Mahmoud

2017-05-01

In this paper, our aim is to analyze geographical and temporal variability of disease incidence when spatio-temporal count data have excess zeros. To that end, we consider random effects in zero-inflated Poisson models to investigate geographical and temporal patterns of disease incidence. Spatio-temporal models that employ conditionally autoregressive smoothing across the spatial dimension and B-spline smoothing over the temporal dimension are proposed. The analysis of these complex models is computationally difficult from the frequentist perspective. On the other hand, the advent of the Markov chain Monte Carlo algorithm has made the Bayesian analysis of complex models computationally convenient. Recently developed data cloning method provides a frequentist approach to mixed models that is also computationally convenient. We propose to use data cloning, which yields to maximum likelihood estimation, to conduct frequentist analysis of zero-inflated spatio-temporal modeling of disease incidence. One of the advantages of the data cloning approach is that the prediction and corresponding standard errors (or prediction intervals) of smoothing disease incidence over space and time is easily obtained. We illustrate our approach using a real dataset of monthly children asthma visits to hospital in the province of Manitoba, Canada, during the period April 2006 to March 2010. Performance of our approach is also evaluated through a simulation study. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Statistical Models for the Analysis of Zero-Inflated Pain Intensity Numeric Rating Scale Data.

PubMed

Goulet, Joseph L; Buta, Eugenia; Bathulapalli, Harini; Gueorguieva, Ralitza; Brandt, Cynthia A

2017-03-01

Pain intensity is often measured in clinical and research settings using the 0 to 10 numeric rating scale (NRS). NRS scores are recorded as discrete values, and in some samples they may display a high proportion of zeroes and a right-skewed distribution. Despite this, statistical methods for normally distributed data are frequently used in the analysis of NRS data. We present results from an observational cross-sectional study examining the association of NRS scores with patient characteristics using data collected from a large cohort of 18,935 veterans in Department of Veterans Affairs care diagnosed with a potentially painful musculoskeletal disorder. The mean (variance) NRS pain was 3.0 (7.5), and 34% of patients reported no pain (NRS = 0). We compared the following statistical models for analyzing NRS scores: linear regression, generalized linear models (Poisson and negative binomial), zero-inflated and hurdle models for data with an excess of zeroes, and a cumulative logit model for ordinal data. We examined model fit, interpretability of results, and whether conclusions about the predictor effects changed across models. In this study, models that accommodate zero inflation provided a better fit than the other models. These models should be considered for the analysis of NRS data with a large proportion of zeroes. We examined and analyzed pain data from a large cohort of veterans with musculoskeletal disorders. We found that many reported no current pain on the NRS on the diagnosis date. We present several alternative statistical methods for the analysis of pain intensity data with a large proportion of zeroes. Published by Elsevier Inc.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory.

PubMed

Lord, Dominique; Washington, Simon P; Ivan, John N

2005-01-01

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states-perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of "excess" zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate

A comparison between Poisson and zero-inflated Poisson regression models with an application to number of black spots in Corriedale sheep

PubMed Central

Naya, Hugo; Urioste, Jorge I; Chang, Yu-Mei; Rodrigues-Motta, Mariana; Kremer, Roberto; Gianola, Daniel

2008-01-01

Dark spots in the fleece area are often associated with dark fibres in wool, which limits its competitiveness with other textile fibres. Field data from a sheep experiment in Uruguay revealed an excess number of zeros for dark spots. We compared the performance of four Poisson and zero-inflated Poisson (ZIP) models under four simulation scenarios. All models performed reasonably well under the same scenario for which the data were simulated. The deviance information criterion favoured a Poisson model with residual, while the ZIP model with a residual gave estimates closer to their true values under all simulation scenarios. Both Poisson and ZIP models with an error term at the regression level performed better than their counterparts without such an error. Field data from Corriedale sheep were analysed with Poisson and ZIP models with residuals. Parameter estimates were similar for both models. Although the posterior distribution of the sire variance was skewed due to a small number of rams in the dataset, the median of this variance suggested a scope for genetic selection. The main environmental factor was the age of the sheep at shearing. In summary, age related processes seem to drive the number of dark spots in this breed of sheep. PMID:18558072

Unified Computational Methods for Regression Analysis of Zero-Inflated and Bound-Inflated Data

PubMed Central

Yang, Yan; Simpson, Douglas

2010-01-01

Bounded data with excess observations at the boundary are common in many areas of application. Various individual cases of inflated mixture models have been studied in the literature for bound-inflated data, yet the computational methods have been developed separately for each type of model. In this article we use a common framework for computing these models, and expand the range of models for both discrete and semi-continuous data with point inflation at the lower boundary. The quasi-Newton and EM algorithms are adapted and compared for estimation of model parameters. The numerical Hessian and generalized Louis method are investigated as means for computing standard errors after optimization. Correlated data are included in this framework via generalized estimating equations. The estimation of parameters and effectiveness of standard errors are demonstrated through simulation and in the analysis of data from an ultrasound bioeffect study. The unified approach enables reliable computation for a wide class of inflated mixture models and comparison of competing models. PMID:20228950

New variable selection methods for zero-inflated count data with applications to the substance abuse field

PubMed Central

Buu, Anne; Johnson, Norman J.; Li, Runze; Tan, Xianming

2011-01-01

Zero-inflated count data are very common in health surveys. This study develops new variable selection methods for the zero-inflated Poisson regression model. Our simulations demonstrate the negative consequences which arise from the ignorance of zero-inflation. Among the competing methods, the one-step SCAD method is recommended because it has the highest specificity, sensitivity, exact fit, and lowest estimation error. The design of the simulations is based on the special features of two large national databases commonly used in the alcoholism and substance abuse field so that our findings can be easily generalized to the real settings. Applications of the methodology are demonstrated by empirical analyses on the data from a well-known alcohol study. PMID:21563207

Some findings on zero-inflated and hurdle poisson models for disease mapping.

PubMed

Corpas-Burgos, Francisca; García-Donato, Gonzalo; Martinez-Beneito, Miguel A

2018-05-27

Zero excess in the study of geographically referenced mortality data sets has been the focus of considerable attention in the literature, with zero-inflation being the most common procedure to handle this lack of fit. Although hurdle models have also been used in disease mapping studies, their use is more rare. We show in this paper that models using particular treatments of zero excesses are often required for achieving appropriate fits in regular mortality studies since, otherwise, geographical units with low expected counts are oversmoothed. However, as also shown, an indiscriminate treatment of zero excess may be unnecessary and has a problematic implementation. In this regard, we find that naive zero-inflation and hurdle models, without an explicit modeling of the probabilities of zeroes, do not fix zero excesses problems well enough and are clearly unsatisfactory. Results sharply suggest the need for an explicit modeling of the probabilities that should vary across areal units. Unfortunately, these more flexible modeling strategies can easily lead to improper posterior distributions as we prove in several theoretical results. Those procedures have been repeatedly used in the disease mapping literature, and one should bear these issues in mind in order to propose valid models. We finally propose several valid modeling alternatives according to the results mentioned that are suitable for fitting zero excesses. We show that those proposals fix zero excesses problems and correct the mentioned oversmoothing of risks in low populated units depicting geographic patterns more suited to the data. Copyright © 2018 John Wiley & Sons, Ltd.

Full Bayes Poisson gamma, Poisson lognormal, and zero inflated random effects models: Comparing the precision of crash frequency estimates.

PubMed

Aguero-Valverde, Jonathan

2013-01-01

In recent years, complex statistical modeling approaches have being proposed to handle the unobserved heterogeneity and the excess of zeros frequently found in crash data, including random effects and zero inflated models. This research compares random effects, zero inflated, and zero inflated random effects models using a full Bayes hierarchical approach. The models are compared not just in terms of goodness-of-fit measures but also in terms of precision of posterior crash frequency estimates since the precision of these estimates is vital for ranking of sites for engineering improvement. Fixed-over-time random effects models are also compared to independent-over-time random effects models. For the crash dataset being analyzed, it was found that once the random effects are included in the zero inflated models, the probability of being in the zero state is drastically reduced, and the zero inflated models degenerate to their non zero inflated counterparts. Also by fixing the random effects over time the fit of the models and the precision of the crash frequency estimates are significantly increased. It was found that the rankings of the fixed-over-time random effects models are very consistent among them. In addition, the results show that by fixing the random effects over time, the standard errors of the crash frequency estimates are significantly reduced for the majority of the segments on the top of the ranking. Copyright © 2012 Elsevier Ltd. All rights reserved.

Trending in Probability of Collision Measurements via a Bayesian Zero-Inflated Beta Mixed Model

NASA Technical Reports Server (NTRS)

Vallejo, Jonathon; Hejduk, Matt; Stamey, James

2015-01-01

We investigate the performance of a generalized linear mixed model in predicting the Probabilities of Collision (Pc) for conjunction events. Specifically, we apply this model to the log(sub 10) transformation of these probabilities and argue that this transformation yields values that can be considered bounded in practice. Additionally, this bounded random variable, after scaling, is zero-inflated. Consequently, we model these values using the zero-inflated Beta distribution, and utilize the Bayesian paradigm and the mixed model framework to borrow information from past and current events. This provides a natural way to model the data and provides a basis for answering questions of interest, such as what is the likelihood of observing a probability of collision equal to the effective value of zero on a subsequent observation.

Does attitude matter in computer use in Australian general practice? A zero-inflated Poisson regression analysis.

PubMed

Khan, Asaduzzaman; Western, Mark

The purpose of this study was to explore factors that facilitate or hinder effective use of computers in Australian general medical practice. This study is based on data extracted from a national telephone survey of 480 general practitioners (GPs) across Australia. Clinical functions performed by GPs using computers were examined using a zero-inflated Poisson (ZIP) regression modelling. About 17% of GPs were not using computer for any clinical function, while 18% reported using computers for all clinical functions. The ZIP model showed that computer anxiety was negatively associated with effective computer use, while practitioners' belief about usefulness of computers was positively associated with effective computer use. Being a female GP or working in partnership or group practice increased the odds of effectively using computers for clinical functions. To fully capitalise on the benefits of computer technology, GPs need to be convinced that this technology is useful and can make a difference.

A Zero- and K-Inflated Mixture Model for Health Questionnaire Data

PubMed Central

Finkelman, Matthew D.; Green, Jennifer Greif; Gruber, Michael J.; Zaslavsky, Alan M.

2011-01-01

In psychiatric assessment, Item Response Theory (IRT) is a popular tool to formalize the relation between the severity of a disorder and associated responses to questionnaire items. Practitioners of IRT sometimes make the assumption of normally distributed severities within a population; while convenient, this assumption is often violated when measuring psychiatric disorders. Specifically, there may be a sizable group of respondents whose answers place them at an extreme of the latent trait spectrum. In this article, a zero- and K-inflated mixture model is developed to account for the presence of such respondents. The model is fitted using an expectation-maximization (E-M) algorithm to estimate the percentage of the population at each end of the continuum, concurrently analyzing the remaining “graded component” via IRT. A method to perform factor analysis for only the graded component is introduced. In assessments of oppositional defiant disorder and conduct disorder, the zero- and K-inflated model exhibited better fit than the standard IRT model. PMID:21365673

Item Response Modeling of Multivariate Count Data with Zero Inflation, Maximum Inflation, and Heaping

ERIC Educational Resources Information Center

Magnus, Brooke E.; Thissen, David

2017-01-01

Questionnaires that include items eliciting count responses are becoming increasingly common in psychology. This study proposes methodological techniques to overcome some of the challenges associated with analyzing multivariate item response data that exhibit zero inflation, maximum inflation, and heaping at preferred digits. The modeling…

Hurdle models for multilevel zero-inflated data via h-likelihood.

PubMed

Molas, Marek; Lesaffre, Emmanuel

2010-12-30

Count data often exhibit overdispersion. One type of overdispersion arises when there is an excess of zeros in comparison with the standard Poisson distribution. Zero-inflated Poisson and hurdle models have been proposed to perform a valid likelihood-based analysis to account for the surplus of zeros. Further, data often arise in clustered, longitudinal or multiple-membership settings. The proper analysis needs to reflect the design of a study. Typically random effects are used to account for dependencies in the data. We examine the h-likelihood estimation and inference framework for hurdle models with random effects for complex designs. We extend the h-likelihood procedures to fit hurdle models, thereby extending h-likelihood to truncated distributions. Two applications of the methodology are presented. Copyright © 2010 John Wiley & Sons, Ltd.

Marginalized zero-altered models for longitudinal count data.

PubMed

Tabb, Loni Philip; Tchetgen, Eric J Tchetgen; Wellenius, Greg A; Coull, Brent A

2016-10-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias.

Marginalized zero-altered models for longitudinal count data

PubMed Central

Tabb, Loni Philip; Tchetgen, Eric J. Tchetgen; Wellenius, Greg A.; Coull, Brent A.

2015-01-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias. PMID:27867423

Semiparametric bivariate zero-inflated Poisson models with application to studies of abundance for multiple species

USGS Publications Warehouse

Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.

2012-01-01

Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.

Modeling Zero-Inflated and Overdispersed Count Data: An Empirical Study of School Suspensions

ERIC Educational Resources Information Center

Desjardins, Christopher David

2016-01-01

The purpose of this article is to develop a statistical model that best explains variability in the number of school days suspended. Number of school days suspended is a count variable that may be zero-inflated and overdispersed relative to a Poisson model. Four models were examined: Poisson, negative binomial, Poisson hurdle, and negative…

Zero-Inflated Poisson Modeling of Fall Risk Factors in Community-Dwelling Older Adults.

PubMed

Jung, Dukyoo; Kang, Younhee; Kim, Mi Young; Ma, Rye-Won; Bhandari, Pratibha

2016-02-01

The aim of this study was to identify risk factors for falls among community-dwelling older adults. The study used a cross-sectional descriptive design. Self-report questionnaires were used to collect data from 658 community-dwelling older adults and were analyzed using logistic and zero-inflated Poisson (ZIP) regression. Perceived health status was a significant factor in the count model, and fall efficacy emerged as a significant predictor in the logistic models. The findings suggest that fall efficacy is important for predicting not only faller and nonfaller status but also fall counts in older adults who may or may not have experienced a previous fall. The fall predictors identified in this study--perceived health status and fall efficacy--indicate the need for fall-prevention programs tailored to address both the physical and psychological issues unique to older adults. © The Author(s) 2014.

On performance of parametric and distribution-free models for zero-inflated and over-dispersed count responses.

PubMed

Tang, Wan; Lu, Naiji; Chen, Tian; Wang, Wenjuan; Gunzler, Douglas David; Han, Yu; Tu, Xin M

2015-10-30

Zero-inflated Poisson (ZIP) and negative binomial (ZINB) models are widely used to model zero-inflated count responses. These models extend the Poisson and negative binomial (NB) to address excessive zeros in the count response. By adding a degenerate distribution centered at 0 and interpreting it as describing a non-risk group in the population, the ZIP (ZINB) models a two-component population mixture. As in applications of Poisson and NB, the key difference between ZIP and ZINB is the allowance for overdispersion by the ZINB in its NB component in modeling the count response for the at-risk group. Overdispersion arising in practice too often does not follow the NB, and applications of ZINB to such data yield invalid inference. If sources of overdispersion are known, other parametric models may be used to directly model the overdispersion. Such models too are subject to assumed distributions. Further, this approach may not be applicable if information about the sources of overdispersion is unavailable. In this paper, we propose a distribution-free alternative and compare its performance with these popular parametric models as well as a moment-based approach proposed by Yu et al. [Statistics in Medicine 2013; 32: 2390-2405]. Like the generalized estimating equations, the proposed approach requires no elaborate distribution assumptions. Compared with the approach of Yu et al., it is more robust to overdispersed zero-inflated responses. We illustrate our approach with both simulated and real study data. Copyright © 2015 John Wiley & Sons, Ltd.

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications.

PubMed

Van den Berge, Koen; Perraudeau, Fanny; Soneson, Charlotte; Love, Michael I; Risso, Davide; Vert, Jean-Philippe; Robinson, Mark D; Dudoit, Sandrine; Clement, Lieven

2018-02-26

Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to cope with zero inflation. Recent evaluations, however, have shown that dedicated scRNA-seq tools provide no advantage compared to traditional bulk RNA-seq tools. We introduce a weighting strategy, based on a zero-inflated negative binomial model, that identifies excess zero counts and generates gene- and cell-specific weights to unlock bulk RNA-seq DE pipelines for zero-inflated data, boosting performance for scRNA-seq.

Bayesian spatiotemporal analysis of zero-inflated biological population density data by a delta-normal spatiotemporal additive model.

PubMed

Arcuti, Simona; Pollice, Alessio; Ribecco, Nunziata; D'Onghia, Gianfranco

2016-03-01

We evaluate the spatiotemporal changes in the density of a particular species of crustacean known as deep-water rose shrimp, Parapenaeus longirostris, based on biological sample data collected during trawl surveys carried out from 1995 to 2006 as part of the international project MEDITS (MEDiterranean International Trawl Surveys). As is the case for many biological variables, density data are continuous and characterized by unusually large amounts of zeros, accompanied by a skewed distribution of the remaining values. Here we analyze the normalized density data by a Bayesian delta-normal semiparametric additive model including the effects of covariates, using penalized regression with low-rank thin-plate splines for nonlinear spatial and temporal effects. Modeling the zero and nonzero values by two joint processes, as we propose in this work, allows to obtain great flexibility and easily handling of complex likelihood functions, avoiding inaccurate statistical inferences due to misclassification of the high proportion of exact zeros in the model. Bayesian model estimation is obtained by Markov chain Monte Carlo simulations, suitably specifying the complex likelihood function of the zero-inflated density data. The study highlights relevant nonlinear spatial and temporal effects and the influence of the annual Mediterranean oscillations index and of the sea surface temperature on the distribution of the deep-water rose shrimp density. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits.

PubMed

Neelon, Brian; Chang, Howard H; Ling, Qiang; Hastings, Nicole S

2016-12-01

Motivated by a study exploring spatiotemporal trends in emergency department use, we develop a class of two-part hurdle models for the analysis of zero-inflated areal count data. The models consist of two components-one for the probability of any emergency department use and one for the number of emergency department visits given use. Through a hierarchical structure, the models incorporate both patient- and region-level predictors, as well as spatially and temporally correlated random effects for each model component. The random effects are assigned multivariate conditionally autoregressive priors, which induce dependence between the components and provide spatial and temporal smoothing across adjacent spatial units and time periods, resulting in improved inferences. To accommodate potential overdispersion, we consider a range of parametric specifications for the positive counts, including truncated negative binomial and generalized Poisson distributions. We adopt a Bayesian inferential approach, and posterior computation is handled conveniently within standard Bayesian software. Our results indicate that the negative binomial and generalized Poisson hurdle models vastly outperform the Poisson hurdle model, demonstrating that overdispersed hurdle models provide a useful approach to analyzing zero-inflated spatiotemporal data. © The Author(s) 2014.

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts.

PubMed

Preisser, John S; Long, D Leann; Stamm, John W

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two data sets, one consisting of fictional dmft counts in 2 groups and the other on DMFS among schoolchildren from a randomized clinical trial comparing 3 toothpaste formulations to prevent incident dental caries, are analyzed with negative binomial hurdle, zero-inflated negative binomial, and marginalized zero-inflated negative binomial models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the randomized clinical trial were similar despite their distinctive interpretations. The choice of statistical model class should match the study's purpose, while accounting for the broad decline in children's caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. © 2017 S. Karger AG, Basel.

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts

PubMed Central

Preisser, John S.; Long, D. Leann; Stamm, John W.

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two datasets, one consisting of fictional dmft counts in two groups and the other on DMFS among schoolchildren from a randomized clinical trial (RCT) comparing three toothpaste formulations to prevent incident dental caries, are analysed with negative binomial hurdle (NBH), zero-inflated negative binomial (ZINB), and marginalized zero-inflated negative binomial (MZINB) models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the RCT were similar despite their distinctive interpretations. Choice of statistical model class should match the study’s purpose, while accounting for the broad decline in children’s caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. PMID:28291962

Multinomial model and zero-inflated gamma model to study time spent on leisure time physical activity: an example of ELSA-Brasil.

PubMed

Nobre, Aline Araújo; Carvalho, Marilia Sá; Griep, Rosane Härter; Fonseca, Maria de Jesus Mendes da; Melo, Enirtes Caetano Prates; Santos, Itamar de Souza; Chor, Dora

2017-08-17

To compare two methodological approaches: the multinomial model and the zero-inflated gamma model, evaluating the factors associated with the practice and amount of time spent on leisure time physical activity. Data collected from 14,823 baseline participants in the Longitudinal Study of Adult Health (ELSA-Brasil - Estudo Longitudinal de Saúde do Adulto ) have been analysed. Regular leisure time physical activity has been measured using the leisure time physical activity module of the International Physical Activity Questionnaire. The explanatory variables considered were gender, age, education level, and annual per capita family income. The main advantage of the zero-inflated gamma model over the multinomial model is that it estimates mean time (minutes per week) spent on leisure time physical activity. For example, on average, men spent 28 minutes/week longer on leisure time physical activity than women did. The most sedentary groups were young women with low education level and income. The zero-inflated gamma model, which is rarely used in epidemiological studies, can give more appropriate answers in several situations. In our case, we have obtained important information on the main determinants of the duration of leisure time physical activity. This information can help guide efforts towards the most vulnerable groups since physical inactivity is associated with different diseases and even premature death.

A review on models for count data with extra zeros

NASA Astrophysics Data System (ADS)

Zamri, Nik Sarah Nik; Zamzuri, Zamira Hasanah

2017-04-01

Typically, the zero inflated models are usually used in modelling count data with excess zeros. The existence of the extra zeros could be structural zeros or random which occur by chance. These types of data are commonly found in various disciplines such as finance, insurance, biomedical, econometrical, ecology, and health sciences. As found in the literature, the most popular zero inflated models used are zero inflated Poisson and zero inflated negative binomial. Recently, more complex models have been developed to account for overdispersion and unobserved heterogeneity. In addition, more extended distributions are also considered in modelling data with this feature. In this paper, we review related literature, provide a recent development and summary on models for count data with extra zeros.

Zero inflation in ordinal data: Incorporating susceptibility to response through the use of a mixture model

PubMed Central

Kelley, Mary E.; Anderson, Stewart J.

2008-01-01

Summary The aim of the paper is to produce a methodology that will allow users of ordinal scale data to more accurately model the distribution of ordinal outcomes in which some subjects are susceptible to exhibiting the response and some are not (i.e., the dependent variable exhibits zero inflation). This situation occurs with ordinal scales in which there is an anchor that represents the absence of the symptom or activity, such as “none”, “never” or “normal”, and is particularly common when measuring abnormal behavior, symptoms, and side effects. Due to the unusually large number of zeros, traditional statistical tests of association can be non-informative. We propose a mixture model for ordinal data with a built-in probability of non-response that allows modeling of the range (e.g., severity) of the scale, while simultaneously modeling the presence/absence of the symptom. Simulations show that the model is well behaved and a likelihood ratio test can be used to choose between the zero-inflated and the traditional proportional odds model. The model, however, does have minor restrictions on the nature of the covariates that must be satisfied in order for the model to be identifiable. The method is particularly relevant for public health research such as large epidemiological surveys where more careful documentation of the reasons for response may be difficult. PMID:18351711

Zero-state Markov switching count-data models: an empirical assessment.

PubMed

Malyshkina, Nataliya V; Mannering, Fred L

2010-01-01

In this study, a two-state Markov switching count-data model is proposed as an alternative to zero-inflated models to account for the preponderance of zeros sometimes observed in transportation count data, such as the number of accidents occurring on a roadway segment over some period of time. For this accident-frequency case, zero-inflated models assume the existence of two states: one of the states is a zero-accident count state, which has accident probabilities that are so low that they cannot be statistically distinguished from zero, and the other state is a normal-count state, in which counts can be non-negative integers that are generated by some counting process, for example, a Poisson or negative binomial. While zero-inflated models have come under some criticism with regard to accident-frequency applications - one fact is undeniable - in many applications they provide a statistically superior fit to the data. The Markov switching approach we propose seeks to overcome some of the criticism associated with the zero-accident state of the zero-inflated model by allowing individual roadway segments to switch between zero and normal-count states over time. An important advantage of this Markov switching approach is that it allows for the direct statistical estimation of the specific roadway-segment state (i.e., zero-accident or normal-count state) whereas traditional zero-inflated models do not. To demonstrate the applicability of this approach, a two-state Markov switching negative binomial model (estimated with Bayesian inference) and standard zero-inflated negative binomial models are estimated using five-year accident frequencies on Indiana interstate highway segments. It is shown that the Markov switching model is a viable alternative and results in a superior statistical fit relative to the zero-inflated models.

Zero adjusted models with applications to analysing helminths count data.

PubMed

Chipeta, Michael G; Ngwira, Bagrey M; Simoonga, Christopher; Kazembe, Lawrence N

2014-11-27

It is common in public health and epidemiology that the outcome of interest is counts of events occurrence. Analysing these data using classical linear models is mostly inappropriate, even after transformation of outcome variables due to overdispersion. Zero-adjusted mixture count models such as zero-inflated and hurdle count models are applied to count data when over-dispersion and excess zeros exist. Main objective of the current paper is to apply such models to analyse risk factors associated with human helminths (S. haematobium) particularly in a case where there's a high proportion of zero counts. The data were collected during a community-based randomised control trial assessing the impact of mass drug administration (MDA) with praziquantel in Malawi, and a school-based cross sectional epidemiology survey in Zambia. Count data models including traditional (Poisson and negative binomial) models, zero modified models (zero inflated Poisson and zero inflated negative binomial) and hurdle models (Poisson logit hurdle and negative binomial logit hurdle) were fitted and compared. Using Akaike information criteria (AIC), the negative binomial logit hurdle (NBLH) and zero inflated negative binomial (ZINB) showed best performance in both datasets. With regards to zero count capturing, these models performed better than other models. This paper showed that zero modified NBLH and ZINB models are more appropriate methods for the analysis of data with excess zeros. The choice between the hurdle and zero-inflated models should be based on the aim and endpoints of the study.

Mapping species abundance by a spatial zero-inflated Poisson model: a case study in the Wadden Sea, the Netherlands.

PubMed

Lyashevska, Olga; Brus, Dick J; van der Meer, Jaap

2016-01-01

The objective of the study was to provide a general procedure for mapping species abundance when data are zero-inflated and spatially correlated counts. The bivalve species Macoma balthica was observed on a 500×500 m grid in the Dutch part of the Wadden Sea. In total, 66% of the 3451 counts were zeros. A zero-inflated Poisson mixture model was used to relate counts to environmental covariates. Two models were considered, one with relatively fewer covariates (model "small") than the other (model "large"). The models contained two processes: a Bernoulli (species prevalence) and a Poisson (species intensity, when the Bernoulli process predicts presence). The model was used to make predictions for sites where only environmental data are available. Predicted prevalences and intensities show that the model "small" predicts lower mean prevalence and higher mean intensity, than the model "large". Yet, the product of prevalence and intensity, which might be called the unconditional intensity, is very similar. Cross-validation showed that the model "small" performed slightly better, but the difference was small. The proposed methodology might be generally applicable, but is computer intensive.

Analyzing Propensity Matched Zero-Inflated Count Outcomes in Observational Studies

PubMed Central

DeSantis, Stacia M.; Lazaridis, Christos; Ji, Shuang; Spinale, Francis G.

2013-01-01

Determining the effectiveness of different treatments from observational data, which are characterized by imbalance between groups due to lack of randomization, is challenging. Propensity matching is often used to rectify imbalances among prognostic variables. However, there are no guidelines on how appropriately to analyze group matched data when the outcome is a zero inflated count. In addition, there is debate over whether to account for correlation of responses induced by matching, and/or whether to adjust for variables used in generating the propensity score in the final analysis. The aim of this research is to compare covariate unadjusted and adjusted zero-inflated Poisson models that do and do not account for the correlation. A simulation study is conducted, demonstrating that it is necessary to adjust for potential residual confounding, but that accounting for correlation is less important. The methods are applied to a biomedical research data set. PMID:24298197

Poisson Mixture Regression Models for Heart Disease Prediction.

PubMed

Mufudza, Chipo; Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

Poisson Mixture Regression Models for Heart Disease Prediction

PubMed Central

Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Treesearch

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

Classifying next-generation sequencing data using a zero-inflated Poisson model.

PubMed

Zhou, Yan; Wan, Xiang; Zhang, Baoxue; Tong, Tiejun

2018-04-15

With the development of high-throughput techniques, RNA-sequencing (RNA-seq) is becoming increasingly popular as an alternative for gene expression analysis, such as RNAs profiling and classification. Identifying which type of diseases a new patient belongs to with RNA-seq data has been recognized as a vital problem in medical research. As RNA-seq data are discrete, statistical methods developed for classifying microarray data cannot be readily applied for RNA-seq data classification. Witten proposed a Poisson linear discriminant analysis (PLDA) to classify the RNA-seq data in 2011. Note, however, that the count datasets are frequently characterized by excess zeros in real RNA-seq or microRNA sequence data (i.e. when the sequence depth is not enough or small RNAs with the length of 18-30 nucleotides). Therefore, it is desired to develop a new model to analyze RNA-seq data with an excess of zeros. In this paper, we propose a Zero-Inflated Poisson Logistic Discriminant Analysis (ZIPLDA) for RNA-seq data with an excess of zeros. The new method assumes that the data are from a mixture of two distributions: one is a point mass at zero, and the other follows a Poisson distribution. We then consider a logistic relation between the probability of observing zeros and the mean of the genes and the sequencing depth in the model. Simulation studies show that the proposed method performs better than, or at least as well as, the existing methods in a wide range of settings. Two real datasets including a breast cancer RNA-seq dataset and a microRNA-seq dataset are also analyzed, and they coincide with the simulation results that our proposed method outperforms the existing competitors. The software is available at http://www.math.hkbu.edu.hk/∼tongt. xwan@comp.hkbu.edu.hk or tongt@hkbu.edu.hk. Supplementary data are available at Bioinformatics online.

Applying the zero-inflated Poisson model with random effects to detect abnormal rises in school absenteeism indicating infectious diseases outbreak.

PubMed

Song, X X; Zhao, Q; Tao, T; Zhou, C M; Diwan, V K; Xu, B

2018-05-30

Records of absenteeism from primary schools are valuable data for infectious diseases surveillance. However, the analysis of the absenteeism is complicated by the data features of clustering at zero, non-independence and overdispersion. This study aimed to generate an appropriate model to handle the absenteeism data collected in a European Commission granted project for infectious disease surveillance in rural China and to evaluate the validity and timeliness of the resulting model for early warnings of infectious disease outbreak. Four steps were taken: (1) building a 'well-fitting' model by the zero-inflated Poisson model with random effects (ZIP-RE) using the absenteeism data from the first implementation year; (2) applying the resulting model to predict the 'expected' number of absenteeism events in the second implementation year; (3) computing the differences between the observations and the expected values (O-E values) to generate an alternative series of data; (4) evaluating the early warning validity and timeliness of the observational data and model-based O-E values via the EARS-3C algorithms with regard to the detection of real cluster events. The results indicate that ZIP-RE and its corresponding O-E values could improve the detection of aberrations, reduce the false-positive signals and are applicable to the zero-inflated data.

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany

PubMed Central

Wang, Zhu; Shuangge, Ma; Wang, Ching-Yun

2017-01-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using an open-source R package mpath. PMID:26059498

Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Suparti; Wahyu Utami, Tiani

2018-03-01

Regression analysis is an analysis to model the relationship between response variables and predictor variables. The parametric approach to the regression model is very strict with the assumption, but nonparametric regression model isn’t need assumption of model. Time series data is the data of a variable that is observed based on a certain time, so if the time series data wanted to be modeled by regression, then we should determined the response and predictor variables first. Determination of the response variable in time series is variable in t-th (yt), while the predictor variable is a significant lag. In nonparametric regression modeling, one developing approach is to use the Fourier series approach. One of the advantages of nonparametric regression approach using Fourier series is able to overcome data having trigonometric distribution. In modeling using Fourier series needs parameter of K. To determine the number of K can be used Generalized Cross Validation method. In inflation modeling for the transportation sector, communication and financial services using Fourier series yields an optimal K of 120 parameters with R-square 99%. Whereas if it was modeled by multiple linear regression yield R-square 90%.

Conditional modeling of antibody titers using a zero-inflated poisson random effects model: application to Fabrazyme.

PubMed

Bonate, Peter L; Sung, Crystal; Welch, Karen; Richards, Susan

2009-10-01

Patients that are exposed to biotechnology-derived therapeutics often develop antibodies to the therapeutic, the magnitude of which is assessed by measuring antibody titers. A statistical approach for analyzing antibody titer data conditional on seroconversion is presented. The proposed method is to first transform the antibody titer data based on a geometric series using a common ratio of 2 and a scale factor of 50 and then analyze the exponent using a zero-inflated or hurdle model assuming a Poisson or negative binomial distribution with random effects to account for patient heterogeneity. Patient specific covariates can be used to model the probability of developing an antibody response, i.e., seroconversion, as well as the magnitude of the antibody titer itself. The method was illustrated using antibody titer data from 87 male seroconverted Fabry patients receiving Fabrazyme. Titers from five clinical trials were collected over 276 weeks of therapy with anti-Fabrazyme IgG titers ranging from 100 to 409,600 after exclusion of seronegative patients. The best model to explain seroconversion was a zero-inflated Poisson (ZIP) model where cumulative dose (under a constant dose regimen of dosing every 2 weeks) influenced the probability of seroconversion. There was an 80% chance of seroconversion when the cumulative dose reached 210 mg (90% confidence interval: 194-226 mg). No difference in antibody titers was noted between Japanese or Western patients. Once seroconverted, antibody titers did not remain constant but decreased in an exponential manner from an initial magnitude to a new lower steady-state value. The expected titer after the new steady-state titer had been achieved was 870 (90% CI: 630-1109). The half-life to the new steady-state value after seroconversion was 44 weeks (90% CI: 17-70 weeks). Time to seroconversion did not appear to be correlated with titer at the time of seroconversion. The method can be adequately used to model antibody titer data.

Three-part joint modeling methods for complex functional data mixed with zero-and-one-inflated proportions and zero-inflated continuous outcomes with skewness.

PubMed

Li, Haocheng; Staudenmayer, John; Wang, Tianying; Keadle, Sarah Kozey; Carroll, Raymond J

2018-02-20

We take a functional data approach to longitudinal studies with complex bivariate outcomes. This work is motivated by data from a physical activity study that measured 2 responses over time in 5-minute intervals. One response is the proportion of time active in each interval, a continuous proportions with excess zeros and ones. The other response, energy expenditure rate in the interval, is a continuous variable with excess zeros and skewness. This outcome is complex because there are 3 possible activity patterns in each interval (inactive, partially active, and completely active), and those patterns, which are observed, induce both nonrandom and random associations between the responses. More specifically, the inactive pattern requires a zero value in both the proportion for active behavior and the energy expenditure rate; a partially active pattern means that the proportion of activity is strictly between zero and one and that the energy expenditure rate is greater than zero and likely to be moderate, and the completely active pattern means that the proportion of activity is exactly one, and the energy expenditure rate is greater than zero and likely to be higher. To address these challenges, we propose a 3-part functional data joint modeling approach. The first part is a continuation-ratio model to reorder the ordinal valued 3 activity patterns. The second part models the proportions when they are in interval (0,1). The last component specifies the skewed continuous energy expenditure rate with Box-Cox transformations when they are greater than zero. In this 3-part model, the regression structures are specified as smooth curves measured at various time points with random effects that have a correlation structure. The smoothed random curves for each variable are summarized using a few important principal components, and the association of the 3 longitudinal components is modeled through the association of the principal component scores. The difficulties in

Extending the Applicability of the Generalized Likelihood Function for Zero-Inflated Data Series

NASA Astrophysics Data System (ADS)

Oliveira, Debora Y.; Chaffe, Pedro L. B.; Sá, João. H. M.

2018-03-01

Proper uncertainty estimation for data series with a high proportion of zero and near zero observations has been a challenge in hydrologic studies. This technical note proposes a modification to the Generalized Likelihood function that accounts for zero inflation of the error distribution (ZI-GL). We compare the performance of the proposed ZI-GL with the original Generalized Likelihood function using the entire data series (GL) and by simply suppressing zero observations (GLy>0). These approaches were applied to two interception modeling examples characterized by data series with a significant number of zeros. The ZI-GL produced better uncertainty ranges than the GL as measured by the precision, reliability and volumetric bias metrics. The comparison between ZI-GL and GLy>0 highlights the need for further improvement in the treatment of residuals from near zero simulations when a linear heteroscedastic error model is considered. Aside from the interception modeling examples illustrated herein, the proposed ZI-GL may be useful for other hydrologic studies, such as for the modeling of the runoff generation in hillslopes and ephemeral catchments.

A tutorial on count regression and zero-altered count models for longitudinal substance use data

PubMed Central

Atkins, David C.; Baldwin, Scott A.; Zheng, Cheng; Gallop, Robert J.; Neighbors, Clayton

2012-01-01

Critical research questions in the study of addictive behaviors concern how these behaviors change over time - either as the result of intervention or in naturalistic settings. The combination of count outcomes that are often strongly skewed with many zeroes (e.g., days using, number of total drinks, number of drinking consequences) with repeated assessments (e.g., longitudinal follow-up after intervention or daily diary data) present challenges for data analyses. The current article provides a tutorial on methods for analyzing longitudinal substance use data, focusing on Poisson, zero-inflated, and hurdle mixed models, which are types of hierarchical or multilevel models. Two example datasets are used throughout, focusing on drinking-related consequences following an intervention and daily drinking over the past 30 days, respectively. Both datasets as well as R, SAS, Mplus, Stata, and SPSS code showing how to fit the models are available on a supplemental website. PMID:22905895

A time-varying effect model for examining group differences in trajectories of zero-inflated count outcomes with applications in substance abuse research.

PubMed

Yang, Songshan; Cranford, James A; Jester, Jennifer M; Li, Runze; Zucker, Robert A; Buu, Anne

2017-02-28

This study proposes a time-varying effect model for examining group differences in trajectories of zero-inflated count outcomes. The motivating example demonstrates that this zero-inflated Poisson model allows investigators to study group differences in different aspects of substance use (e.g., the probability of abstinence and the quantity of alcohol use) simultaneously. The simulation study shows that the accuracy of estimation of trajectory functions improves as the sample size increases; the accuracy under equal group sizes is only higher when the sample size is small (100). In terms of the performance of the hypothesis testing, the type I error rates are close to their corresponding significance levels under all settings. Furthermore, the power increases as the alternative hypothesis deviates more from the null hypothesis, and the rate of this increasing trend is higher when the sample size is larger. Moreover, the hypothesis test for the group difference in the zero component tends to be less powerful than the test for the group difference in the Poisson component. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany.

PubMed

Wang, Zhu; Ma, Shuangge; Wang, Ching-Yun

2015-09-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD), and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, but also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using the open-source R package mpath. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Regular exercise and related factors in patients with Parkinson's disease: Applying zero-inflated negative binomial modeling of exercise count data.

PubMed

Lee, JuHee; Park, Chang Gi; Choi, Moonki

2016-05-01

This study was conducted to identify risk factors that influence regular exercise among patients with Parkinson's disease in Korea. Parkinson's disease is prevalent in the elderly, and may lead to a sedentary lifestyle. Exercise can enhance physical and psychological health. However, patients with Parkinson's disease are less likely to exercise than are other populations due to physical disability. A secondary data analysis and cross-sectional descriptive study were conducted. A convenience sample of 106 patients with Parkinson's disease was recruited at an outpatient neurology clinic of a tertiary hospital in Korea. Demographic characteristics, disease-related characteristics (including disease duration and motor symptoms), self-efficacy for exercise, balance, and exercise level were investigated. Negative binomial regression and zero-inflated negative binomial regression for exercise count data were utilized to determine factors involved in exercise. The mean age of participants was 65.85 ± 8.77 years, and the mean duration of Parkinson's disease was 7.23 ± 6.02 years. Most participants indicated that they engaged in regular exercise (80.19%). Approximately half of participants exercised at least 5 days per week for 30 min, as recommended (51.9%). Motor symptoms were a significant predictor of exercise in the count model, and self-efficacy for exercise was a significant predictor of exercise in the zero model. Severity of motor symptoms was related to frequency of exercise. Self-efficacy contributed to the probability of exercise. Symptom management and improvement of self-efficacy for exercise are important to encourage regular exercise in patients with Parkinson's disease. Copyright © 2015 Elsevier Inc. All rights reserved.

MIXED MODEL AND ESTIMATING EQUATION APPROACHES FOR ZERO INFLATION IN CLUSTERED BINARY RESPONSE DATA WITH APPLICATION TO A DATING VIOLENCE STUDY1

PubMed Central

Fulton, Kara A.; Liu, Danping; Haynie, Denise L.; Albert, Paul S.

2016-01-01

The NEXT Generation Health study investigates the dating violence of adolescents using a survey questionnaire. Each student is asked to affirm or deny multiple instances of violence in his/her dating relationship. There is, however, evidence suggesting that students not in a relationship responded to the survey, resulting in excessive zeros in the responses. This paper proposes likelihood-based and estimating equation approaches to analyze the zero-inflated clustered binary response data. We adopt a mixed model method to account for the cluster effect, and the model parameters are estimated using a maximum-likelihood (ML) approach that requires a Gaussian–Hermite quadrature (GHQ) approximation for implementation. Since an incorrect assumption on the random effects distribution may bias the results, we construct generalized estimating equations (GEE) that do not require the correct specification of within-cluster correlation. In a series of simulation studies, we examine the performance of ML and GEE methods in terms of their bias, efficiency and robustness. We illustrate the importance of properly accounting for this zero inflation by reanalyzing the NEXT data where this issue has previously been ignored. PMID:26937263

The effect of a major cigarette price change on smoking behavior in california: a zero-inflated negative binomial model.

PubMed

Sheu, Mei-Ling; Hu, Teh-Wei; Keeler, Theodore E; Ong, Michael; Sung, Hai-Yen

2004-08-01

The objective of this paper is to determine the price sensitivity of smokers in their consumption of cigarettes, using evidence from a major increase in California cigarette prices due to Proposition 10 and the Tobacco Settlement. The study sample consists of individual survey data from Behavioral Risk Factor Survey (BRFS) and price data from the Bureau of Labor Statistics between 1996 and 1999. A zero-inflated negative binomial (ZINB) regression model was applied for the statistical analysis. The statistical model showed that price did not have an effect on reducing the estimated prevalence of smoking. However, it indicated that among smokers the price elasticity was at the level of -0.46 and statistically significant. Since smoking prevalence is significantly lower than it was a decade ago, price increases are becoming less effective as an inducement for hard-core smokers to quit, although they may respond by decreasing consumption. For those who only smoke occasionally (many of them being young adults) price increases alone may not be an effective inducement to quit smoking. Additional underlying behavioral factors need to be identified so that more effective anti-smoking strategies can be developed.

Zero-Inflated Models for Identifying Relationships Between Body Mass Index and Gastroesophageal Reflux Symptoms: A Nationwide Population-Based Study in China.

PubMed

Xu, Qin; Zhang, Wei; Zhang, Tianyi; Zhang, Ruijie; Zhao, Yanfang; Zhang, Yuan; Guo, Yibin; Wang, Rui; Ma, Xiuqiang; He, Jia

2016-07-01

That obesity leads to gastroesophageal reflux is a widespread notion. However, scientific evidence for this association is limited, with no rigorous epidemiological approach conducted to address this question. This study examined the relationship between body mass index (BMI) and gastroesophageal reflux symptoms in a large population-representative sample from China. We performed a cross-sectional study in an age- and gender-stratified random sample of the population of five central regions in China. Participants aged 18-80 years completed a general information questionnaire and a Chinese version of the Reflux Disease Questionnaire. The zero-inflated Poisson regression model estimated the relationship between body mass index and gastroesophageal reflux symptoms. Overall, 16,091 (89.4 %) of the 18,000 eligible participants responded. 638 (3.97 %) and 1738 (10.81 %) experienced at least weekly heartburn and weekly acid regurgitation, respectively. After adjusting for potential risk factors in the zero-inflated part, the frequency [odds ratio (OR) 0.66, 95 % confidence interval (95 % CI) 0.50-0.86, p = 0.002] and severity (OR 0.66, 95 % CI 0.50-088, p = 0.004) of heartburn in obese participants were statistically significant compared to those in normal participants. In the Poisson part, the frequency of acid regurgitation, overweight (OR 1.10, 95 % CI 1.01-1.21, p = 0.038) and obesity (OR 1.19, 95 % CI 1.04-1.37, p = 0.013) were statistically significant. BMI was strongly and positively related to the frequency and severity of gastroesophageal reflux symptoms. Additionally, gender exerted strong specific effects on the relationship between BMI and gastroesophageal reflux symptoms. The severity and frequency of heartburn were positively correlated with obesity. This relationship was presented distinct in male participants only.

Analyzing hospitalization data: potential limitations of Poisson regression.

PubMed

Weaver, Colin G; Ravani, Pietro; Oliver, Matthew J; Austin, Peter C; Quinn, Robert R

2015-08-01

Poisson regression is commonly used to analyze hospitalization data when outcomes are expressed as counts (e.g. number of days in hospital). However, data often violate the assumptions on which Poisson regression is based. More appropriate extensions of this model, while available, are rarely used. We compared hospitalization data between 206 patients treated with hemodialysis (HD) and 107 treated with peritoneal dialysis (PD) using Poisson regression and compared results from standard Poisson regression with those obtained using three other approaches for modeling count data: negative binomial (NB) regression, zero-inflated Poisson (ZIP) regression and zero-inflated negative binomial (ZINB) regression. We examined the appropriateness of each model and compared the results obtained with each approach. During a mean 1.9 years of follow-up, 183 of 313 patients (58%) were never hospitalized (indicating an excess of 'zeros'). The data also displayed overdispersion (variance greater than mean), violating another assumption of the Poisson model. Using four criteria, we determined that the NB and ZINB models performed best. According to these two models, patients treated with HD experienced similar hospitalization rates as those receiving PD {NB rate ratio (RR): 1.04 [bootstrapped 95% confidence interval (CI): 0.49-2.20]; ZINB summary RR: 1.21 (bootstrapped 95% CI 0.60-2.46)}. Poisson and ZIP models fit the data poorly and had much larger point estimates than the NB and ZINB models [Poisson RR: 1.93 (bootstrapped 95% CI 0.88-4.23); ZIP summary RR: 1.84 (bootstrapped 95% CI 0.88-3.84)]. We found substantially different results when modeling hospitalization data, depending on the approach used. Our results argue strongly for a sound model selection process and improved reporting around statistical methods used for modeling count data. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Distribution-free Inference of Zero-inated Binomial Data for Longitudinal Studies.

PubMed

He, H; Wang, W J; Hu, J; Gallop, R; Crits-Christoph, P; Xia, Y L

2015-10-01

Count reponses with structural zeros are very common in medical and psychosocial research, especially in alcohol and HIV research, and the zero-inflated poisson (ZIP) and zero-inflated negative binomial (ZINB) models are widely used for modeling such outcomes. However, as alcohol drinking outcomes such as days of drinkings are counts within a given period, their distributions are bounded above by an upper limit (total days in the period) and thus inherently follow a binomial or zero-inflated binomial (ZIB) distribution, rather than a Poisson or zero-inflated Poisson (ZIP) distribution, in the presence of structural zeros. In this paper, we develop a new semiparametric approach for modeling zero-inflated binomial (ZIB)-like count responses for cross-sectional as well as longitudinal data. We illustrate this approach with both simulated and real study data.

Empirical null estimation using zero-inflated discrete mixture distributions and its application to protein domain data.

PubMed

Gauran, Iris Ivy M; Park, Junyong; Lim, Johan; Park, DoHwan; Zylstra, John; Peterson, Thomas; Kann, Maricel; Spouge, John L

2017-09-22

In recent mutation studies, analyses based on protein domain positions are gaining popularity over gene-centric approaches since the latter have limitations in considering the functional context that the position of the mutation provides. This presents a large-scale simultaneous inference problem, with hundreds of hypothesis tests to consider at the same time. This article aims to select significant mutation counts while controlling a given level of Type I error via False Discovery Rate (FDR) procedures. One main assumption is that the mutation counts follow a zero-inflated model in order to account for the true zeros in the count model and the excess zeros. The class of models considered is the Zero-inflated Generalized Poisson (ZIGP) distribution. Furthermore, we assumed that there exists a cut-off value such that smaller counts than this value are generated from the null distribution. We present several data-dependent methods to determine the cut-off value. We also consider a two-stage procedure based on screening process so that the number of mutations exceeding a certain value should be considered as significant mutations. Simulated and protein domain data sets are used to illustrate this procedure in estimation of the empirical null using a mixture of discrete distributions. Overall, while maintaining control of the FDR, the proposed two-stage testing procedure has superior empirical power. 2017 The Authors. Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

GMPR: A robust normalization method for zero-inflated count data with application to microbiome sequencing data.

PubMed

Chen, Li; Reeve, James; Zhang, Lujun; Huang, Shengbing; Wang, Xuefeng; Chen, Jun

2018-01-01

Normalization is the first critical step in microbiome sequencing data analysis used to account for variable library sizes. Current RNA-Seq based normalization methods that have been adapted for microbiome data fail to consider the unique characteristics of microbiome data, which contain a vast number of zeros due to the physical absence or under-sampling of the microbes. Normalization methods that specifically address the zero-inflation remain largely undeveloped. Here we propose geometric mean of pairwise ratios-a simple but effective normalization method-for zero-inflated sequencing data such as microbiome data. Simulation studies and real datasets analyses demonstrate that the proposed method is more robust than competing methods, leading to more powerful detection of differentially abundant taxa and higher reproducibility of the relative abundances of taxa.

Protection from annual flooding is correlated with increased cholera prevalence in Bangladesh: a zero-inflated regression analysis.

PubMed

Carrel, Margaret; Voss, Paul; Streatfield, Peter K; Yunus, Mohammad; Emch, Michael

2010-03-22

Alteration of natural or historical aquatic flows can have unintended consequences for regions where waterborne diseases are endemic and where the epidemiologic implications of such change are poorly understood. The implementation of flood protection measures for a portion of an intensely monitored population in Matlab, Bangladesh, allows us to examine whether cholera outcomes respond positively or negatively to measures designed to control river flooding. Using a zero inflated negative binomial model, we examine how selected covariates can simultaneously account for household clusters reporting no cholera from those with positive counts as well as distinguishing residential areas with low counts from areas with high cholera counts. Our goal is to examine how residence within or outside a flood protected area interacts with the probability of cholera presence and the effect of flood protection on the magnitude of cholera prevalence. In Matlab, living in a household that is protected from annual monsoon flooding appears to have no significant effect on whether the household experiences cholera, net of other covariates. However, counter-intuitively, among households where cholera is reported, living within the flood protected region significantly increases the number of cholera cases. The construction of dams or other water impoundment strategies for economic or social motives can have profound and unanticipated consequences for waterborne disease. Our results indicate that the construction of a flood control structure in rural Bangladesh is correlated with an increase in cholera cases for residents protected from annual monsoon flooding. Such a finding requires attention from both the health community and from governments and non-governmental organizations involved in ongoing water management schemes.

Some considerations for excess zeroes in substance abuse research.

PubMed

Bandyopadhyay, Dipankar; DeSantis, Stacia M; Korte, Jeffrey E; Brady, Kathleen T

2011-09-01

Count data collected in substance abuse research often come with an excess of "zeroes," which are typically handled using zero-inflated regression models. However, there is a need to consider the design aspects of those studies before using such a statistical model to ascertain the sources of zeroes. We sought to illustrate hurdle models as alternatives to zero-inflated models to validate a two-stage decision-making process in situations of "excess zeroes." We use data from a study of 45 cocaine-dependent subjects where the primary scientific question was to evaluate whether study participation influences drug-seeking behavior. The outcome, "the frequency (count) of cocaine use days per week," is bounded (ranging from 0 to 7). We fit and compare binomial, Poisson, negative binomial, and the hurdle version of these models to study the effect of gender, age, time, and study participation on cocaine use. The hurdle binomial model provides the best fit. Gender and time are not predictive of use. Higher odds of use versus no use are associated with age; however once use is experienced, odds of further use decrease with increase in age. Participation was associated with higher odds of no-cocaine use; once there is use, participation reduced the odds of further use. Age and study participation are significantly predictive of cocaine-use behavior. The two-stage decision process as modeled by a hurdle binomial model (appropriate for bounded count data with excess zeroes) provides interesting insights into the study of covariate effects on count responses of substance use, when all enrolled subjects are believed to be "at-risk" of use.

Disease Mapping of Zero-excessive Mesothelioma Data in Flanders

PubMed Central

Neyens, Thomas; Lawson, Andrew B.; Kirby, Russell S.; Nuyts, Valerie; Watjou, Kevin; Aregay, Mehreteab; Carroll, Rachel; Nawrot, Tim S.; Faes, Christel

2016-01-01

Purpose To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion. Methods The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero-inflation and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature. Results The results indicate that hurdle models with a random effects term accounting for extra-variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra-variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra-variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary. Conclusions Models taking into account zero-inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this. PMID:27908590

Disease mapping of zero-excessive mesothelioma data in Flanders.

PubMed

Neyens, Thomas; Lawson, Andrew B; Kirby, Russell S; Nuyts, Valerie; Watjou, Kevin; Aregay, Mehreteab; Carroll, Rachel; Nawrot, Tim S; Faes, Christel

2017-01-01

To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion. The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero inflation, and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion, and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature. The results indicate that hurdle models with a random effects term accounting for extra variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary. Models taking into account zero inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this. Copyright © 2016 Elsevier Inc. All rights reserved.

Zero-inflated modeling of fish catch per unit area resulting from multiple gears: Application to channel catfish and shovelnose sturgeon in the Missouri River

USGS Publications Warehouse

Arab, A.; Wildhaber, M.L.; Wikle, C.K.; Gentry, C.N.

2008-01-01

Fisheries studies often employ multiple gears that result in large percentages of zero values. We considered a zero-inflated Poisson (ZIP) model with random effects to address these excessive zeros. By employing a Bayesian ZIP model that simultaneously incorporates data from multiple gears to analyze data from the Missouri River, we were able to compare gears and make more year, segment, and macrohabitat comparisons than did the original data analysis. For channel catfish Ictalurus punctatus, our results rank (highest to lowest) the mean catch per unit area (CPUA) for gears (beach seine, benthic trawl, electrofishing, and drifting trammel net); years (1998 and 1997); macrohabitats (tributary mouth, connected secondary channel, nonconnected secondary channel, and bend); and river segment zones (channelized, inter-reservoir, and least-altered). For shovelnose sturgeon Scaphirhynchus platorynchus, the mean CPUA was significantly higher for benthic trawls and drifting trammel nets; 1998 and 1997; tributary mouths, bends, and connected secondary channels; and some channelized or least-altered inter-reservoir segments. One important advantage of our approach is the ability to reliably infer patterns of relative abundance by means of multiple gears without using gear efficiencies. ?? Copyright by the American Fisheries Society 2008.

Antibiotic Resistances in Livestock: A Comparative Approach to Identify an Appropriate Regression Model for Count Data

PubMed Central

Hüls, Anke; Frömke, Cornelia; Ickstadt, Katja; Hille, Katja; Hering, Johanna; von Münchhausen, Christiane; Hartmann, Maria; Kreienbrock, Lothar

2017-01-01

Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i) to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model) and (ii) to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate model. PMID

Estimation of inflation parameters for Perturbed Power Law model using recent CMB measurements

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

Mukherjee, Suvodip; Das, Santanu; Souradeep, Tarun

2015-01-01

Cosmic Microwave Background (CMB) is an important probe for understanding the inflationary era of the Universe. We consider the Perturbed Power Law (PPL) model of inflation which is a soft deviation from Power Law (PL) inflationary model. This model captures the effect of higher order derivative of Hubble parameter during inflation, which in turn leads to a non-zero effective mass m{sub eff} for the inflaton field. The higher order derivatives of Hubble parameter at leading order sources constant difference in the spectral index for scalar and tensor perturbation going beyond PL model of inflation. PPL model have two observable independentmore » parameters, namely spectral index for tensor perturbation ν{sub t} and change in spectral index for scalar perturbation ν{sub st} to explain the observed features in the scalar and tensor power spectrum of perturbation. From the recent measurements of CMB power spectra by WMAP, Planck and BICEP-2 for temperature and polarization, we estimate the feasibility of PPL model with standard ΛCDM model. Although BICEP-2 claimed a detection of r=0.2, estimates of dust contamination provided by Planck have left open the possibility that only upper bound on r will be expected in a joint analysis. As a result we consider different upper bounds on the value of r and show that PPL model can explain a lower value of tensor to scalar ratio (r<0.1 or r<0.01) for a scalar spectral index of n{sub s}=0.96 by having a non-zero value of effective mass of the inflaton field m{sup 2}{sub eff}/H{sup 2}. The analysis with WP + Planck likelihood shows a non-zero detection of m{sup 2}{sub eff}/H{sup 2} with 5.7 σ and 8.1 σ respectively for r<0.1 and r<0.01. Whereas, with BICEP-2 likelihood m{sup 2}{sub eff}/H{sup 2} = −0.0237 ± 0.0135 which is consistent with zero.« less

Estimation of inflation parameters for Perturbed Power Law model using recent CMB measurements

NASA Astrophysics Data System (ADS)

Mukherjee, Suvodip; Das, Santanu; Joy, Minu; Souradeep, Tarun

2015-01-01

Cosmic Microwave Background (CMB) is an important probe for understanding the inflationary era of the Universe. We consider the Perturbed Power Law (PPL) model of inflation which is a soft deviation from Power Law (PL) inflationary model. This model captures the effect of higher order derivative of Hubble parameter during inflation, which in turn leads to a non-zero effective mass meff for the inflaton field. The higher order derivatives of Hubble parameter at leading order sources constant difference in the spectral index for scalar and tensor perturbation going beyond PL model of inflation. PPL model have two observable independent parameters, namely spectral index for tensor perturbation νt and change in spectral index for scalar perturbation νst to explain the observed features in the scalar and tensor power spectrum of perturbation. From the recent measurements of CMB power spectra by WMAP, Planck and BICEP-2 for temperature and polarization, we estimate the feasibility of PPL model with standard ΛCDM model. Although BICEP-2 claimed a detection of r=0.2, estimates of dust contamination provided by Planck have left open the possibility that only upper bound on r will be expected in a joint analysis. As a result we consider different upper bounds on the value of r and show that PPL model can explain a lower value of tensor to scalar ratio (r<0.1 or r<0.01) for a scalar spectral index of ns=0.96 by having a non-zero value of effective mass of the inflaton field m2eff/H2. The analysis with WP + Planck likelihood shows a non-zero detection of m2eff/H2 with 5.7 σ and 8.1 σ respectively for r<0.1 and r<0.01. Whereas, with BICEP-2 likelihood m2eff/H2 = -0.0237 ± 0.0135 which is consistent with zero.

An application of a zero-inflated lifetime distribution with multiple and incomplete data sources

DOE PAGES

Hamada, M. S.; Margevicius, K. J.

2016-02-11

In this study, we analyze data sampled from a population of parts in which an associated anomaly can occur at assembly or after assembly. Using a zero-inflated lifetime distribution to fit left-censored and right-censored data as well data from a supplementary sample, we make predictions about the proportion of the population with anomalies today and in the future. Goodness-of-fit is also addressed.

Weibull mixture regression for marginal inference in zero-heavy continuous outcomes.

PubMed

Gebregziabher, Mulugeta; Voronca, Delia; Teklehaimanot, Abeba; Santa Ana, Elizabeth J

2017-06-01

Continuous outcomes with preponderance of zero values are ubiquitous in data that arise from biomedical studies, for example studies of addictive disorders. This is known to lead to violation of standard assumptions in parametric inference and enhances the risk of misleading conclusions unless managed properly. Two-part models are commonly used to deal with this problem. However, standard two-part models have limitations with respect to obtaining parameter estimates that have marginal interpretation of covariate effects which are important in many biomedical applications. Recently marginalized two-part models are proposed but their development is limited to log-normal and log-skew-normal distributions. Thus, in this paper, we propose a finite mixture approach, with Weibull mixture regression as a special case, to deal with the problem. We use extensive simulation study to assess the performance of the proposed model in finite samples and to make comparisons with other family of models via statistical information and mean squared error criteria. We demonstrate its application on real data from a randomized controlled trial of addictive disorders. Our results show that a two-component Weibull mixture model is preferred for modeling zero-heavy continuous data when the non-zero part are simulated from Weibull or similar distributions such as Gamma or truncated Gauss.

The Application of Censored Regression Models in Low Streamflow Analyses

NASA Astrophysics Data System (ADS)

Kroll, C.; Luz, J.

2003-12-01

Estimation of low streamflow statistics at gauged and ungauged river sites is often a daunting task. This process is further confounded by the presence of intermittent streamflows, where streamflow is sometimes reported as zero, within a region. Streamflows recorded as zero may be zero, or may be less than the measurement detection limit. Such data is often referred to as censored data. Numerous methods have been developed to characterize intermittent streamflow series. Logit regression has been proposed to develop regional models of the probability annual lowflows series (such as 7-day lowflows) are zero. In addition, Tobit regression, a method of regression that allows for censored dependent variables, has been proposed for lowflow regional regression models in regions where the lowflow statistic of interest estimated as zero at some sites in the region. While these methods have been proposed, their use in practice has been limited. Here a delete-one jackknife simulation is presented to examine the performance of Logit and Tobit models of 7-day annual minimum flows in 6 USGS water resource regions in the United States. For the Logit model, an assessment is made of whether sites are correctly classified as having at least 10% of 7-day annual lowflows equal to zero. In such a situation, the 7-day, 10-year lowflow (Q710), a commonly employed low streamflow statistic, would be reported as zero. For the Tobit model, a comparison is made between results from the Tobit model, and from performing either ordinary least squares (OLS) or principal component regression (PCR) after the zero sites are dropped from the analysis. Initial results for the Logit model indicate this method to have a high probability of correctly classifying sites into groups with Q710s as zero and non-zero. Initial results also indicate the Tobit model produces better results than PCR and OLS when more than 5% of the sites in the region have Q710 values calculated as zero.

A smooth exit from eternal inflation?

NASA Astrophysics Data System (ADS)

Hawking, S. W.; Hertog, Thomas

2018-04-01

The usual theory of inflation breaks down in eternal inflation. We derive a dual description of eternal inflation in terms of a deformed Euclidean CFT located at the threshold of eternal inflation. The partition function gives the amplitude of different geometries of the threshold surface in the no-boundary state. Its local and global behavior in dual toy models shows that the amplitude is low for surfaces which are not nearly conformal to the round three-sphere and essentially zero for surfaces with negative curvature. Based on this we conjecture that the exit from eternal inflation does not produce an infinite fractal-like multiverse, but is finite and reasonably smooth.

Impact of multicollinearity on small sample hydrologic regression models

NASA Astrophysics Data System (ADS)

Kroll, Charles N.; Song, Peter

2013-06-01

Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

Two-Part and Related Regression Models for Longitudinal Data

PubMed Central

Farewell, V.T.; Long, D.L.; Tom, B.D.M.; Yiu, S.; Su, L.

2017-01-01

Statistical models that involve a two-part mixture distribution are applicable in a variety of situations. Frequently, the two parts are a model for the binary response variable and a model for the outcome variable that is conditioned on the binary response. Two common examples are zero-inflated or hurdle models for count data and two-part models for semicontinuous data. Recently, there has been particular interest in the use of these models for the analysis of repeated measures of an outcome variable over time. The aim of this review is to consider motivations for the use of such models in this context and to highlight the central issues that arise with their use. We examine two-part models for semicontinuous and zero-heavy count data, and we also consider models for count data with a two-part random effects distribution. PMID:28890906

Bayesian hierarchical modelling of continuous non‐negative longitudinal data with a spike at zero: An application to a study of birds visiting gardens in winter

PubMed Central

Buckland, Stephen T.; King, Ruth; Toms, Mike P.

2015-01-01

The development of methods for dealing with continuous data with a spike at zero has lagged behind those for overdispersed or zero‐inflated count data. We consider longitudinal ecological data corresponding to an annual average of 26 weekly maximum counts of birds, and are hence effectively continuous, bounded below by zero but also with a discrete mass at zero. We develop a Bayesian hierarchical Tweedie regression model that can directly accommodate the excess number of zeros common to this type of data, whilst accounting for both spatial and temporal correlation. Implementation of the model is conducted in a Markov chain Monte Carlo (MCMC) framework, using reversible jump MCMC to explore uncertainty across both parameter and model spaces. This regression modelling framework is very flexible and removes the need to make strong assumptions about mean‐variance relationships a priori. It can also directly account for the spike at zero, whilst being easily applicable to other types of data and other model formulations. Whilst a correlative study such as this cannot prove causation, our results suggest that an increase in an avian predator may have led to an overall decrease in the number of one of its prey species visiting garden feeding stations in the United Kingdom. This may reflect a change in behaviour of house sparrows to avoid feeding stations frequented by sparrowhawks, or a reduction in house sparrow population size as a result of sparrowhawk increase. PMID:25737026

Bayesian hierarchical modelling of continuous non-negative longitudinal data with a spike at zero: An application to a study of birds visiting gardens in winter.

PubMed

Swallow, Ben; Buckland, Stephen T; King, Ruth; Toms, Mike P

2016-03-01

The development of methods for dealing with continuous data with a spike at zero has lagged behind those for overdispersed or zero-inflated count data. We consider longitudinal ecological data corresponding to an annual average of 26 weekly maximum counts of birds, and are hence effectively continuous, bounded below by zero but also with a discrete mass at zero. We develop a Bayesian hierarchical Tweedie regression model that can directly accommodate the excess number of zeros common to this type of data, whilst accounting for both spatial and temporal correlation. Implementation of the model is conducted in a Markov chain Monte Carlo (MCMC) framework, using reversible jump MCMC to explore uncertainty across both parameter and model spaces. This regression modelling framework is very flexible and removes the need to make strong assumptions about mean-variance relationships a priori. It can also directly account for the spike at zero, whilst being easily applicable to other types of data and other model formulations. Whilst a correlative study such as this cannot prove causation, our results suggest that an increase in an avian predator may have led to an overall decrease in the number of one of its prey species visiting garden feeding stations in the United Kingdom. This may reflect a change in behaviour of house sparrows to avoid feeding stations frequented by sparrowhawks, or a reduction in house sparrow population size as a result of sparrowhawk increase. © 2015 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quasiopen inflation

NASA Astrophysics Data System (ADS)

García-Bellido, Juan; Garriga, Jaume; Montes, Xavier

1998-04-01

We show that a large class of two-field models of single-bubble open inflation does not lead to infinite open universes, as was previously thought, but to an ensemble of very large but finite inflating ``islands.'' The reason is that the quantum tunneling responsible for the nucleation of the bubble does not occur simultaneously along both field directions and equal-time hypersurfaces in the open universe are not synchronized with equal-density or fixed-field hypersurfaces. The most probable tunneling trajectory corresponds to a zero value of the inflaton field; large values, necessary for the second period of inflation inside the bubble, only arise as localized fluctuations. The interior of each nucleated bubble will contain an infinite number of such inflating regions of comoving size of order γ-1, where γ is the supercurvature eigenvalue, which depends on the parameters of the model. Each one of these islands will be a quasi-open universe. Since the volume of the hyperboloid is infinite, inflating islands with all possible values of the field at their center will be realized inside of a single bubble. We may happen to live in one of those patches of comoving size d<~γ-1, where the universe appears to be open. In particular, we consider the ``supernatural'' model proposed by Linde and Mezhlumian. There, an approximate U(1) symmetry is broken by a tunneling field in a first order phase transition, and slow-roll inflation inside the nucleated bubble is driven by the pseudo Goldstone field. We find that the excitations of the pseudo Goldstone field produced by the nucleation and subsequent expansion of the bubble place severe constraints on this model. We also discuss the coupled and uncoupled two-field models.

A new multivariate zero-adjusted Poisson model with applications to biomedicine.

PubMed

Liu, Yin; Tian, Guo-Liang; Tang, Man-Lai; Yuen, Kam Chuen

2018-05-25

Recently, although advances were made on modeling multivariate count data, existing models really has several limitations: (i) The multivariate Poisson log-normal model (Aitchison and Ho, ) cannot be used to fit multivariate count data with excess zero-vectors; (ii) The multivariate zero-inflated Poisson (ZIP) distribution (Li et al., 1999) cannot be used to model zero-truncated/deflated count data and it is difficult to apply to high-dimensional cases; (iii) The Type I multivariate zero-adjusted Poisson (ZAP) distribution (Tian et al., 2017) could only model multivariate count data with a special correlation structure for random components that are all positive or negative. In this paper, we first introduce a new multivariate ZAP distribution, based on a multivariate Poisson distribution, which allows the correlations between components with a more flexible dependency structure, that is some of the correlation coefficients could be positive while others could be negative. We then develop its important distributional properties, and provide efficient statistical inference methods for multivariate ZAP model with or without covariates. Two real data examples in biomedicine are used to illustrate the proposed methods. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparing statistical methods for analyzing skewed longitudinal count data with many zeros: an example of smoking cessation.

PubMed

Xie, Haiyi; Tao, Jill; McHugo, Gregory J; Drake, Robert E

2013-07-01

Count data with skewness and many zeros are common in substance abuse and addiction research. Zero-adjusting models, especially zero-inflated models, have become increasingly popular in analyzing this type of data. This paper reviews and compares five mixed-effects Poisson family models commonly used to analyze count data with a high proportion of zeros by analyzing a longitudinal outcome: number of smoking quit attempts from the New Hampshire Dual Disorders Study. The findings of our study indicated that count data with many zeros do not necessarily require zero-inflated or other zero-adjusting models. For rare event counts or count data with small means, a simpler model such as the negative binomial model may provide a better fit. Copyright © 2013 Elsevier Inc. All rights reserved.

Inflation model selection meets dark radiation

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

Tram, Thomas; Vallance, Robert; Vennin, Vincent, E-mail: thomas.tram@port.ac.uk, E-mail: robert.vallance@student.manchester.ac.uk, E-mail: vincent.vennin@port.ac.uk

2017-01-01

We investigate how inflation model selection is affected by the presence of additional free-streaming relativistic degrees of freedom, i.e. dark radiation. We perform a full Bayesian analysis of both inflation parameters and cosmological parameters taking reheating into account self-consistently. We compute the Bayesian evidence for a few representative inflation scenarios in both the standard ΛCDM model and an extension including dark radiation parametrised by its effective number of relativistic species N {sub eff}. Using a minimal dataset (Planck low-ℓ polarisation, temperature power spectrum and lensing reconstruction), we find that the observational status of most inflationary models is unchanged. The exceptionsmore » are potentials such as power-law inflation that predict large values for the scalar spectral index that can only be realised when N {sub eff} is allowed to vary. Adding baryon acoustic oscillations data and the B-mode data from BICEP2/Keck makes power-law inflation disfavoured, while adding local measurements of the Hubble constant H {sub 0} makes power-law inflation slightly favoured compared to the best single-field plateau potentials. This illustrates how the dark radiation solution to the H {sub 0} tension would have deep consequences for inflation model selection.« less

Modeling zero-modified count and semicontinuous data in health services research Part 1: background and overview.

PubMed

Neelon, Brian; O'Malley, A James; Smith, Valerie A

2016-11-30

Health services data often contain a high proportion of zeros. In studies examining patient hospitalization rates, for instance, many patients will have no hospitalizations, resulting in a count of zero. When the number of zeros is greater or less than expected under a standard count model, the data are said to be zero modified relative to the standard model. A similar phenomenon arises with semicontinuous data, which are characterized by a spike at zero followed by a continuous distribution with positive support. When analyzing zero-modified count and semicontinuous data, flexible mixture distributions are often needed to accommodate both the excess zeros and the typically skewed distribution of nonzero values. Various models have been introduced over the past three decades to accommodate such data, including hurdle models, zero-inflated models, and two-part semicontinuous models. This tutorial describes recent modeling strategies for zero-modified count and semicontinuous data and highlights their role in health services research studies. Part 1 of the tutorial, presented here, provides a general overview of the topic. Part 2, appearing as a companion piece in this issue of Statistics in Medicine, discusses three case studies illustrating applications of the methods to health services research. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Bayesian Estimation of Multivariate Latent Regression Models: Gauss versus Laplace

ERIC Educational Resources Information Center

Culpepper, Steven Andrew; Park, Trevor

2017-01-01

A latent multivariate regression model is developed that employs a generalized asymmetric Laplace (GAL) prior distribution for regression coefficients. The model is designed for high-dimensional applications where an approximate sparsity condition is satisfied, such that many regression coefficients are near zero after accounting for all the model…

Inflation in the standard cosmological model

NASA Astrophysics Data System (ADS)

Uzan, Jean-Philippe

2015-12-01

The inflationary paradigm is now part of the standard cosmological model as a description of its primordial phase. While its original motivation was to solve the standard problems of the hot big bang model, it was soon understood that it offers a natural theory for the origin of the large-scale structure of the universe. Most models rely on a slow-rolling scalar field and enjoy very generic predictions. Besides, all the matter of the universe is produced by the decay of the inflaton field at the end of inflation during a phase of reheating. These predictions can be (and are) tested from their imprint of the large-scale structure and in particular the cosmic microwave background. Inflation stands as a window in physics where both general relativity and quantum field theory are at work and which can be observationally studied. It connects cosmology with high-energy physics. Today most models are constructed within extensions of the standard model, such as supersymmetry or string theory. Inflation also disrupts our vision of the universe, in particular with the ideas of chaotic inflation and eternal inflation that tend to promote the image of a very inhomogeneous universe with fractal structure on a large scale. This idea is also at the heart of further speculations, such as the multiverse. This introduction summarizes the connections between inflation and the hot big bang model and details the basics of its dynamics and predictions. xml:lang="fr"

Homogeneous cosmological models and new inflation

NASA Technical Reports Server (NTRS)

Turner, Michael S.; Widrow, Lawrence M.

1986-01-01

The promise of the inflationary-universe scenario is to free the present state of the universe from extreme dependence upon initial data. Paradoxically, inflation is usually analyzed in the context of the homogeneous and isotropic Robertson-Walker cosmological models. It is shown that all but a small subset of the homogeneous models undergo inflation. Any initial anisotropy is so strongly damped that if sufficient inflation occurs to solve the flatness and horizon problems, the universe today would still be very isotropic.

Toward inflation models compatible with the no-boundary proposal

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

Hwang, Dong-il; Yeom, Dong-han, E-mail: dongil.j.hwang@gmail.com, E-mail: innocent.yeom@gmail.com

2014-06-01

In this paper, we investigate various inflation models in the context of the no-boundary proposal. We propose that a good inflation model should satisfy three conditions: observational constraints, plausible initial conditions, and naturalness of the model. For various inflation models, we assign the probability to each initial condition using the no-boundary proposal and define a quantitative standard, typicality, to check whether the model satisfies the observational constraints with probable initial conditions. There are three possible ways to satisfy the typicality criterion: there was pre-inflation near the high energy scale, the potential is finely tuned or the inflationary field space ismore » unbounded, or there are sufficient number of fields that contribute to inflation. The no-boundary proposal rejects some of naive inflation models, explains some of traditional doubts on inflation, and possibly, can have observational consequences.« less

Modeling zero-modified count and semicontinuous data in health services research part 2: case studies.

PubMed

Neelon, Brian; O'Malley, A James; Smith, Valerie A

2016-11-30

This article is the second installment of a two-part tutorial on the analysis of zero-modified count and semicontinuous data. Part 1, which appears as a companion piece in this issue of Statistics in Medicine, provides a general background and overview of the topic, with particular emphasis on applications to health services research. Here, we present three case studies highlighting various approaches for the analysis of zero-modified data. The first case study describes methods for analyzing zero-inflated longitudinal count data. Case study 2 considers the use of hurdle models for the analysis of spatiotemporal count data. The third case study discusses an application of marginalized two-part models to the analysis of semicontinuous health expenditure data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A Linear Regression Model Identifying the Primary Factors Contributing to Maintenance Man Hours for the C-17 Globemaster III in the Air National Guard

DTIC Science & Technology

2012-06-15

Maintenance AFSCs ................................................................................................. 14 2. Variation Inflation Factors...total variability in the data. It is an indication of how much of the   20    variation in the data can be accounted for in the regression model. In... Variation Inflation Factors for each independent variable (predictor) as regressed against all of the other independent variables in the model. The

Comments on SUSY Inflation Models on the Brane

NASA Astrophysics Data System (ADS)

Lee, Lu-Yun; Cheung, Kingman; Lin, Chia-Min

In this paper we consider a class of inflation models on the brane where the dominant part of the inflaton scalar potential does not depend on the inflaton field value during inflation. In particular, we consider supernatural inflation, its hilltop version, A-term inflation, and supersymmetric (SUSY) D- and F-term hybrid inflation on the brane. We show that the parameter space can be broadened, the inflation scale generally can be lowered, and still possible to have the spectral index ns = 0.96.

Genericness of inflation in isotropic loop quantum cosmology.

PubMed

Date, Ghanashyam; Hossain, Golam Mortuza

2005-01-14

Nonperturbative corrections from loop quantum cosmology (LQC) to the scalar matter sector are already known to imply inflation. We prove that the LQC modified scalar field generates exponential inflation in the small scale factor regime, for all positive definite potentials, independent of initial conditions and independent of ambiguity parameters. For positive semidefinite potentials it is always possible to choose, without fine-tuning, a value of one of the ambiguity parameters such that exponential inflation results, provided zeros of the potential are approached at most as a power law in the scale factor. In conjunction with the generic occurrence of bounce at small volumes, particle horizon is absent, thus eliminating the horizon problem of the standard big bang model.

An analysis of input errors in precipitation-runoff models using regression with errors in the independent variables

USGS Publications Warehouse

Troutman, Brent M.

1982-01-01

Errors in runoff prediction caused by input data errors are analyzed by treating precipitation-runoff models as regression (conditional expectation) models. Independent variables of the regression consist of precipitation and other input measurements; the dependent variable is runoff. In models using erroneous input data, prediction errors are inflated and estimates of expected storm runoff for given observed input variables are biased. This bias in expected runoff estimation results in biased parameter estimates if these parameter estimates are obtained by a least squares fit of predicted to observed runoff values. The problems of error inflation and bias are examined in detail for a simple linear regression of runoff on rainfall and for a nonlinear U.S. Geological Survey precipitation-runoff model. Some implications for flood frequency analysis are considered. A case study using a set of data from Turtle Creek near Dallas, Texas illustrates the problems of model input errors.

Does money matter in inflation forecasting?

NASA Astrophysics Data System (ADS)

Binner, J. M.; Tino, P.; Tepper, J.; Anderson, R.; Jones, B.; Kendall, G.

2010-11-01

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two nonlinear techniques, namely, recurrent neural networks and kernel recursive least squares regression-techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naïve random walk model. The best models were nonlinear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. Beyond its economic findings, our study is in the tradition of physicists’ long-standing interest in the interconnections among statistical mechanics, neural networks, and related nonparametric statistical methods, and suggests potential avenues of extension for such studies.

Inflation in the mixed Higgs-R2 model

NASA Astrophysics Data System (ADS)

He, Minxi; Starobinsky, Alexei A.; Yokoyama, Jun'ichi

2018-05-01

We analyze a two-field inflationary model consisting of the Ricci scalar squared (R2) term and the standard Higgs field non-minimally coupled to gravity in addition to the Einstein R term. Detailed analysis of the power spectrum of this model with mass hierarchy is presented, and we find that one can describe this model as an effective single-field model in the slow-roll regime with a modified sound speed. The scalar spectral index predicted by this model coincides with those given by the R2 inflation and the Higgs inflation implying that there is a close relation between this model and the R2 inflation already in the original (Jordan) frame. For a typical value of the self-coupling of the standard Higgs field at the high energy scale of inflation, the role of the Higgs field in parameter space involved is to modify the scalaron mass, so that the original mass parameter in the R2 inflation can deviate from its standard value when non-minimal coupling between the Ricci scalar and the Higgs field is large enough.

A simple, approximate model of parachute inflation

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

Macha, J.M.

1992-11-01

A simple, approximate model of parachute inflation is described. The model is based on the traditional, practical treatment of the fluid resistance of rigid bodies in nonsteady flow, with appropriate extensions to accommodate the change in canopy inflated shape. Correlations for the steady drag and steady radial force as functions of the inflated radius are required as input to the dynamic model. In a novel approach, the radial force is expressed in terms of easily obtainable drag and reefing fine tension measurements. A series of wind tunnel experiments provides the needed correlations. Coefficients associated with the added mass of fluidmore » are evaluated by calibrating the model against an extensive and reliable set of flight data. A parameter is introduced which appears to universally govern the strong dependence of the axial added mass coefficient on motion history. Through comparisons with flight data, the model is shown to realistically predict inflation forces for ribbon and ringslot canopies over a wide range of sizes and deployment conditions.« less

A simple, approximate model of parachute inflation

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

Macha, J.M.

1992-01-01

A simple, approximate model of parachute inflation is described. The model is based on the traditional, practical treatment of the fluid resistance of rigid bodies in nonsteady flow, with appropriate extensions to accommodate the change in canopy inflated shape. Correlations for the steady drag and steady radial force as functions of the inflated radius are required as input to the dynamic model. In a novel approach, the radial force is expressed in terms of easily obtainable drag and reefing fine tension measurements. A series of wind tunnel experiments provides the needed correlations. Coefficients associated with the added mass of fluidmore » are evaluated by calibrating the model against an extensive and reliable set of flight data. A parameter is introduced which appears to universally govern the strong dependence of the axial added mass coefficient on motion history. Through comparisons with flight data, the model is shown to realistically predict inflation forces for ribbon and ringslot canopies over a wide range of sizes and deployment conditions.« less

A new approach for handling longitudinal count data with zero-inflation and overdispersion: poisson geometric process model.

PubMed

Wan, Wai-Yin; Chan, Jennifer S K

2009-08-01

For time series of count data, correlated measurements, clustering as well as excessive zeros occur simultaneously in biomedical applications. Ignoring such effects might contribute to misleading treatment outcomes. A generalized mixture Poisson geometric process (GMPGP) model and a zero-altered mixture Poisson geometric process (ZMPGP) model are developed from the geometric process model, which was originally developed for modelling positive continuous data and was extended to handle count data. These models are motivated by evaluating the trend development of new tumour counts for bladder cancer patients as well as by identifying useful covariates which affect the count level. The models are implemented using Bayesian method with Markov chain Monte Carlo (MCMC) algorithms and are assessed using deviance information criterion (DIC).

Effects of categorization method, regression type, and variable distribution on the inflation of Type-I error rate when categorizing a confounding variable.

PubMed

Barnwell-Ménard, Jean-Louis; Li, Qing; Cohen, Alan A

2015-03-15

The loss of signal associated with categorizing a continuous variable is well known, and previous studies have demonstrated that this can lead to an inflation of Type-I error when the categorized variable is a confounder in a regression analysis estimating the effect of an exposure on an outcome. However, it is not known how the Type-I error may vary under different circumstances, including logistic versus linear regression, different distributions of the confounder, and different categorization methods. Here, we analytically quantified the effect of categorization and then performed a series of 9600 Monte Carlo simulations to estimate the Type-I error inflation associated with categorization of a confounder under different regression scenarios. We show that Type-I error is unacceptably high (>10% in most scenarios and often 100%). The only exception was when the variable categorized was a continuous mixture proxy for a genuinely dichotomous latent variable, where both the continuous proxy and the categorized variable are error-ridden proxies for the dichotomous latent variable. As expected, error inflation was also higher with larger sample size, fewer categories, and stronger associations between the confounder and the exposure or outcome. We provide online tools that can help researchers estimate the potential error inflation and understand how serious a problem this is. Copyright © 2014 John Wiley & Sons, Ltd.

Model with two periods of inflation

NASA Astrophysics Data System (ADS)

Schettler, Simon; Schaffner-Bielich, Jürgen

2016-01-01

A scenario with two subsequent periods of inflationary expansion in the very early Universe is examined. The model is based on a potential motivated by symmetries being found in field theory at high energy. For various parameter sets of the potential, the spectra of scalar and tensor perturbations that are expected to originate from this scenario are calculated. Also the beginning of the reheating epoch connecting the second inflation with thermal equilibrium is studied. Perturbations with wavelengths leaving the horizon around the transition between the two inflations are special: It is demonstrated that the power spectrum at such scales deviates significantly from expectations based on measurements of the cosmic microwave background. This supports the conclusion that parameters for which this part of the spectrum leaves observable traces in the cosmic microwave background must be excluded. Parameters entailing a very efficient second inflation correspond to standard small-field inflation and can meet observational constraints. Particular attention is paid to the case where the second inflation leads solely to a shift of the observable spectrum from the first inflation. A viable scenario requires this shift to be small.

Global embedding of fibre inflation models

NASA Astrophysics Data System (ADS)

Cicoli, Michele; Muia, Francesco; Shukla, Pramod

2016-11-01

We present concrete embeddings of fibre inflation models in globally consistent type IIB Calabi-Yau orientifolds with closed string moduli stabilisation. After performing a systematic search through the existing list of toric Calabi-Yau manifolds, we find several examples that reproduce the minimal setup to embed fibre inflation models. This involves Calabi-Yau manifolds with h 1,1 = 3 which are K3 fibrations over a ℙ1 base with an additional shrinkable rigid divisor. We then provide different consistent choices of the underlying brane set-up which generate a non-perturbative superpotential suitable for moduli stabilisation and string loop corrections with the correct form to drive inflation. For each Calabi-Yau orientifold setting, we also compute the effect of higher derivative contributions and study their influence on the inflationary dynamics.

A quantile count model of water depth constraints on Cape Sable seaside sparrows

USGS Publications Warehouse

Cade, B.S.; Dong, Q.

2008-01-01

1. A quantile regression model for counts of breeding Cape Sable seaside sparrows Ammodramus maritimus mirabilis (L.) as a function of water depth and previous year abundance was developed based on extensive surveys, 1992-2005, in the Florida Everglades. The quantile count model extends linear quantile regression methods to discrete response variables, providing a flexible alternative to discrete parametric distributional models, e.g. Poisson, negative binomial and their zero-inflated counterparts. 2. Estimates from our multiplicative model demonstrated that negative effects of increasing water depth in breeding habitat on sparrow numbers were dependent on recent occupation history. Upper 10th percentiles of counts (one to three sparrows) decreased with increasing water depth from 0 to 30 cm when sites were not occupied in previous years. However, upper 40th percentiles of counts (one to six sparrows) decreased with increasing water depth for sites occupied in previous years. 3. Greatest decreases (-50% to -83%) in upper quantiles of sparrow counts occurred as water depths increased from 0 to 15 cm when previous year counts were 1, but a small proportion of sites (5-10%) held at least one sparrow even as water depths increased to 20 or 30 cm. 4. A zero-inflated Poisson regression model provided estimates of conditional means that also decreased with increasing water depth but rates of change were lower and decreased with increasing previous year counts compared to the quantile count model. Quantiles computed for the zero-inflated Poisson model enhanced interpretation of this model but had greater lack-of-fit for water depths > 0 cm and previous year counts 1, conditions where the negative effect of water depths were readily apparent and fitted better with the quantile count model.

Bayesian analysis of zero inflated spatiotemporal HIV/TB child mortality data through the INLA and SPDE approaches: Applied to data observed between 1992 and 2010 in rural North East South Africa

NASA Astrophysics Data System (ADS)

Musenge, Eustasius; Chirwa, Tobias Freeman; Kahn, Kathleen; Vounatsou, Penelope

2013-06-01

Longitudinal mortality data with few deaths usually have problems of zero-inflation. This paper presents and applies two Bayesian models which cater for zero-inflation, spatial and temporal random effects. To reduce the computational burden experienced when a large number of geo-locations are treated as a Gaussian field (GF) we transformed the field to a Gaussian Markov Random Fields (GMRF) by triangulation. We then modelled the spatial random effects using the Stochastic Partial Differential Equations (SPDEs). Inference was done using a computationally efficient alternative to Markov chain Monte Carlo (MCMC) called Integrated Nested Laplace Approximation (INLA) suited for GMRF. The models were applied to data from 71,057 children aged 0 to under 10 years from rural north-east South Africa living in 15,703 households over the years 1992-2010. We found protective effects on HIV/TB mortality due to greater birth weight, older age and more antenatal clinic visits during pregnancy (adjusted RR (95% CI)): 0.73(0.53;0.99), 0.18(0.14;0.22) and 0.96(0.94;0.97) respectively. Therefore childhood HIV/TB mortality could be reduced if mothers are better catered for during pregnancy as this can reduce mother-to-child transmissions and contribute to improved birth weights. The INLA and SPDE approaches are computationally good alternatives in modelling large multilevel spatiotemporal GMRF data structures.

The field-space metric in spiral inflation and related models

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

Erlich, Joshua; Olsen, Jackson; Wang, Zhen

2016-09-22

Multi-field inflation models include a variety of scenarios for how inflation proceeds and ends. Models with the same potential but different kinetic terms are common in the literature. We compare spiral inflation and Dante’s inferno-type models, which differ only in their field-space metric. We justify a single-field effective description in these models and relate the single-field description to a mass-matrix formalism. We note the effects of the nontrivial field-space metric on inflationary observables, and consequently on the viability of these models. We also note a duality between spiral inflation and Dante’s inferno models with different potentials.

Dark energy from gravitoelectromagnetic inflation?

NASA Astrophysics Data System (ADS)

Membiela, F. A.; Bellini, M.

2008-02-01

Gravitoectromagnetic Inflation (GI) was introduced to describe in an unified manner, electromagnetic, gravitatory and inflaton fields from a 5D vacuum state. On the other hand, the primordial origin and evolution of dark energy is today unknown. In this letter we show using GI that the zero modes of some redefined vector fields $B_i=A_i/a$ produced during inflation, could be the source of dark energy in the universe.

Modeling inflation rates and exchange rates in Ghana: application of multivariate GARCH models.

PubMed

Nortey, Ezekiel Nn; Ngoh, Delali D; Doku-Amponsah, Kwabena; Ofori-Boateng, Kenneth

2015-01-01

This paper was aimed at investigating the volatility and conditional relationship among inflation rates, exchange rates and interest rates as well as to construct a model using multivariate GARCH DCC and BEKK models using Ghana data from January 1990 to December 2013. The study revealed that the cumulative depreciation of the cedi to the US dollar from 1990 to 2013 is 7,010.2% and the yearly weighted depreciation of the cedi to the US dollar for the period is 20.4%. There was evidence that, the fact that inflation rate was stable, does not mean that exchange rates and interest rates are expected to be stable. Rather, when the cedi performs well on the forex, inflation rates and interest rates react positively and become stable in the long run. The BEKK model is robust to modelling and forecasting volatility of inflation rates, exchange rates and interest rates. The DCC model is robust to model the conditional and unconditional correlation among inflation rates, exchange rates and interest rates. The BEKK model, which forecasted high exchange rate volatility for the year 2014, is very robust for modelling the exchange rates in Ghana. The mean equation of the DCC model is also robust to forecast inflation rates in Ghana.

Constraints on texture zero and cofactor zero models for neutrino mass

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

Whisnant, K.; Liao, Jiajun; Marfatia, D.

2014-06-24

Imposing a texture or cofactor zero on the neutrino mass matrix reduces the number of independent parameters from nine to seven. Since five parameters have been measured, only two independent parameters would remain in such models. We find the allowed regions for single texture zero and single cofactor zero models. We also find strong similarities between single texture zero models with one mass hierarchy and single cofactor zero models with the opposite mass hierarchy. We show that this correspondence can be generalized to texture-zero and cofactor-zero models with the same homogeneous costraints on the elements and cofactors.

Inflatable Re-Entry Vehicle Experiment (IRVE) Design Overview

NASA Technical Reports Server (NTRS)

Hughes, Stephen J.; Dillman, Robert A.; Starr, Brett R.; Stephan, Ryan A.; Lindell, Michael C.; Player, Charles J.; Cheatwood, F. McNeil

2005-01-01

integrity when exposed to a relevant dynamic pressure and aerodynamic stability of the inflatable system. Structural integrity and structural response of the inflatable will be verified with photogrammetric measurements of the back side of the aeroshell in flight. Aerodynamic stability as well as drag performance will be verified with on board inertial measurements and radar tracking from multiple ground radar stations. The experiment will yield valuable information about zero-g vacuum deployment dynamics of the flexible inflatable structure with both inertial and photographic measurements. In addition to demonstrating inflatable technology, IRVE will validate structural, aerothermal, and trajectory modeling techniques for the inflatable. Structural response determined from photogrammetrics will validate structural models, skin temperature measurements and additional in-depth temperature measurements will validate material thermal performance models, and on board inertial measurements along with radar tracking from multiple ground radar stations will validate trajectory simulation models.

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model.

PubMed

Kim, Dae-Hwan; Ramjan, Lucie M; Mak, Kwok-Kei

2016-01-01

Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea. A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience. Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes. Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

Replenishment policy for an inventory model under inflation

NASA Astrophysics Data System (ADS)

Singh, Vikramjeet; Saxena, Seema; Singh, Pushpinder; Mishra, Nitin Kumar

2017-07-01

The purpose of replenishment is to keep the flow of inventory in the system. To determine an optimal replenishment policy is a great challenge in developing an inventory model. Inflation is defined as the rate at which the prices of goods and services are rising over a time period. The cost parameters are affected by the rate of inflation. High rate of inflation affects the organizations financial conditions. Based on the above backdrop the present paper proposes the retailers replenishment policy for deteriorating items with different cycle lengths under inflation. The shortages are partially backlogged. At last numerical examples validate the results.

First-order inflation

NASA Technical Reports Server (NTRS)

Kolb, Edward W.

1991-01-01

In the original proposal, inflation occurred in the process of a strongly first-order phase transition. This model was soon demonstrated to be fatally flawed. Subsequent models for inflation involved phase transitions that were second-order, or perhaps weakly first-order; some even involved no phase transition at all. Recently the possibility of inflation during a strongly first-order phase transition has been revived. In this talk I will discuss some models for first-order inflation, and emphasize unique signatures that result if inflation is realized in a first-order transition. Before discussing first-order inflation, I will briefly review some of the history of inflation to demonstrate how first-order inflation differs from other models.

Minimal supergravity models of inflation

NASA Astrophysics Data System (ADS)

Ferrara, Sergio; Kallosh, Renata; Linde, Andrei; Porrati, Massimo

2013-10-01

We present a superconformal master action for a class of supergravity models with one arbitrary function defining the Jordan frame. It leads to a gauge-invariant action for a real vector multiplet, which upon gauge fixing describes a massive vector multiplet, or to a dual formulation with a linear multiplet and a massive tensor field. In both cases the models have one real scalar, the inflaton, naturally suited for single-field inflation. Vectors and tensors required by supersymmetry to complement a single real scalar do not acquire vacuum expectation values during inflation, so there is no need to stabilize the extra scalars that are always present in the theories with chiral matter multiplets. The new class of models can describe any inflaton potential that vanishes at its minimum and grows monotonically away from the minimum. In this class of supergravity models, one can fit any desirable choice of inflationary parameters ns and r.

Universality of the Volume Bound in Slow-Roll Eternal Inflation

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

Dubovsky, Sergei; Senatore, Leonardo; Villadoro, Giovanni

2012-03-28

It has recently been shown that in single field slow-roll inflation the total volume cannot grow by a factor larger than e{sup S{sub dS}/2} without becoming infinite. The bound is saturated exactly at the phase transition to eternal inflation where the probability to produce infinite volume becomes non zero. We show that the bound holds sharply also in any space-time dimensions, when arbitrary higher-dimensional operators are included and in the multi-field inflationary case. The relation with the entropy of de Sitter and the universality of the bound strengthen the case for a deeper holographic interpretation. As a spin-off we providemore » the formalism to compute the probability distribution of the volume after inflation for generic multi-field models, which might help to address questions about the population of vacua of the landscape during slow-roll inflation.« less

A viable logarithmic f(R) model for inflation

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

Amin, M.; Khalil, S.; Salah, M.

2016-08-18

Inflation in the framework of f(R) modified gravity is revisited. We study the conditions that f(R) should satisfy in order to lead to a viable inflationary model in the original form and in the Einstein frame. Based on these criteria we propose a new logarithmic model as a potential candidate for f(R) theories aiming to describe inflation consistent with observations from Planck satellite (2015). The model predicts scalar spectral index 0.9615

Cumulative sum control charts for monitoring geometrically inflated Poisson processes: An application to infectious disease counts data.

PubMed

Rakitzis, Athanasios C; Castagliola, Philippe; Maravelakis, Petros E

2018-02-01

In this work, we study upper-sided cumulative sum control charts that are suitable for monitoring geometrically inflated Poisson processes. We assume that a process is properly described by a two-parameter extension of the zero-inflated Poisson distribution, which can be used for modeling count data with an excessive number of zero and non-zero values. Two different upper-sided cumulative sum-type schemes are considered, both suitable for the detection of increasing shifts in the average of the process. Aspects of their statistical design are discussed and their performance is compared under various out-of-control situations. Changes in both parameters of the process are considered. Finally, the monitoring of the monthly cases of poliomyelitis in the USA is given as an illustrative example.

False Positives in Multiple Regression: Unanticipated Consequences of Measurement Error in the Predictor Variables

ERIC Educational Resources Information Center

Shear, Benjamin R.; Zumbo, Bruno D.

2013-01-01

Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…

Pseudosmooth tribrid inflation

NASA Astrophysics Data System (ADS)

Antusch, Stefan; Nolde, David; Rehman, Mansoor Ur

2012-08-01

We explore a new class of supersymmetric models of inflation where the inflaton is realised as a combination of a Higgs field and (gauge non-singlet) matter fields, using a ``tribrid'' structure of the superpotential. Inflation is associated with a phase transition around GUT scale energies. The inflationary trajectory already preselects the later vacuum after inflation, which has the advantage of automatically avoiding the production of dangerous topological defects at the end of inflation. While at first sight the models look similar to smooth inflation, they feature a waterfall and are therefore only pseudosmooth. The new class of models offers novel possibilities for realising inflation in close contact with particle physics, for instance with supersymmetric GUTs or with supersymmetric flavour models based on family symmetries.

Supernatural inflation: inflation from supersymmetry with no (very) small parameters

NASA Astrophysics Data System (ADS)

Randall, Lisa; SoljačiĆ, Marin; Guth, Alan H.

1996-02-01

Most models of inflation have small parameters, either to guarantee sufficient inflation or the correct magnitude of the density perturbations. In this paper we show that, in supersymmetric theories with weak-scale supersymmetry breaking, one can construct viable inflationary models in which the requisite parameters appear naturally in the form of the ratio of mass scales that are already present in the theory. Successful inflationary models can be constructed from the flat-direction fields of a renormalizable supersymmetric potential, and such models can be realized even in the context of a simple GUT extension of the MSSM. We evade naive ``naturalness'' arguments by allowing for more than one field to be relevant to inflation, as in ``hybrid inflation'' models, and we argue that this is the most natural possibility if inflation fields are to be associated with flat direction fields of a supersymmetric theory. Such models predict a very low Hubble constant during inflation, of order 103-104 GeV, a scalar density perturbation index n which is very close to or greater than unity, and negligible tensor perturbations. In addition, these models lead to a large spike in the density perturbation spectrum at short wavelengths.

Two-field axion-monodromy hybrid inflation model: Dante's Waterfall

NASA Astrophysics Data System (ADS)

Carone, Christopher D.; Erlich, Joshua; Sensharma, Anuraag; Wang, Zhen

2015-02-01

We describe a hybrid axion-monodromy inflation model motivated by the Dante's Inferno scenario. In Dante's Inferno, a two-field potential features a stable trench along which a linear combination of the two fields slowly rolls, rendering the dynamics essentially identical to that of single-field chaotic inflation. A shift symmetry allows for the Lyth bound to be effectively evaded as in other axion-monodromy models. In our proposal, the potential is concave downward near the origin and the inflaton trajectory is a gradual downward spiral, ending at a point where the trench becomes unstable. There, the fields begin falling rapidly towards the minimum of the potential and inflation terminates as in a hybrid model. We find parameter choices that reproduce observed features of the cosmic microwave background, and discuss our model in light of recent results from the BICEP2 and Planck experiments.

Inflation and dark energy from f(R) gravity

NASA Astrophysics Data System (ADS)

Artymowski, Michał; Lalak, Zygmunt

2014-09-01

The standard Starobinsky inflation has been extended to the R + α Rn - β R2-n model to obtain a stable minimum of the Einstein frame scalar potential of the auxiliary field. As a result we have obtained obtain a scalar potential with non-zero value of residual vacuum energy, which may be a source of Dark Energy. Our results can be easily consistent with PLANCK or BICEP2 data for appropriate choices of the value of n.

A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function

PubMed Central

2012-01-01

Background The EQ-5D is a generic health-related quality of life instrument (five dimensions with three levels, 243 health states), used extensively in cost-utility/cost-effectiveness analyses. EQ-5D health states are assigned values on a scale anchored in perfect health (1) and death (0). The dominant procedure for defining values for EQ-5D health states involves regression modeling. These regression models have typically included a constant term, interpreted as the utility loss associated with any movement away from perfect health. The authors of the United States EQ-5D valuation study replaced this constant with a variable, D1, which corresponds to the number of impaired dimensions beyond the first. The aim of this study was to illustrate how the use of the D1 variable in place of a constant is problematic. Methods We compared the original D1 regression model with a mathematically equivalent model with a constant term. Comparisons included implications for the magnitude and statistical significance of the coefficients, multicollinearity (variance inflation factors, or VIFs), number of calculation steps needed to determine tariff values, and consequences for tariff interpretation. Results Using the D1 variable in place of a constant shifted all dummy variable coefficients away from zero by the value of the constant, greatly increased the multicollinearity of the model (maximum VIF of 113.2 vs. 21.2), and increased the mean number of calculation steps required to determine health state values. Discussion Using the D1 variable in place of a constant constitutes an unnecessary complication of the model, obscures the fact that at least two of the main effect dummy variables are statistically nonsignificant, and complicates and biases interpretation of the tariff algorithm. PMID:22244261

A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function.

PubMed

Rand-Hendriksen, Kim; Augestad, Liv A; Dahl, Fredrik A

2012-01-13

The EQ-5D is a generic health-related quality of life instrument (five dimensions with three levels, 243 health states), used extensively in cost-utility/cost-effectiveness analyses. EQ-5D health states are assigned values on a scale anchored in perfect health (1) and death (0).The dominant procedure for defining values for EQ-5D health states involves regression modeling. These regression models have typically included a constant term, interpreted as the utility loss associated with any movement away from perfect health. The authors of the United States EQ-5D valuation study replaced this constant with a variable, D1, which corresponds to the number of impaired dimensions beyond the first. The aim of this study was to illustrate how the use of the D1 variable in place of a constant is problematic. We compared the original D1 regression model with a mathematically equivalent model with a constant term. Comparisons included implications for the magnitude and statistical significance of the coefficients, multicollinearity (variance inflation factors, or VIFs), number of calculation steps needed to determine tariff values, and consequences for tariff interpretation. Using the D1 variable in place of a constant shifted all dummy variable coefficients away from zero by the value of the constant, greatly increased the multicollinearity of the model (maximum VIF of 113.2 vs. 21.2), and increased the mean number of calculation steps required to determine health state values. Using the D1 variable in place of a constant constitutes an unnecessary complication of the model, obscures the fact that at least two of the main effect dummy variables are statistically nonsignificant, and complicates and biases interpretation of the tariff algorithm.

Seeded hot dark matter models with inflation

NASA Technical Reports Server (NTRS)

Gratsias, John; Scherrer, Robert J.; Steigman, Gary; Villumsen, Jens V.

1993-01-01

We examine massive neutrino (hot dark matter) models for large-scale structure in which the density perturbations are produced by randomly distributed relic seeds and by inflation. Power spectra, streaming velocities, and the Sachs-Wolfe quadrupole fluctuation are derived for this model. We find that the pure seeded hot dark matter model without inflation produces Sachs-Wolfe fluctuations far smaller than those seen by COBE. With the addition of inflationary perturbations, fluctuations consistent with COBE can be produced. The COBE results set the normalization of the inflationary component, which determines the large-scale (about 50/h Mpc) streaming velocities. The normalization of the seed power spectrum is a free parameter, which can be adjusted to obtain the desired fluctuations on small scales. The power spectra produced are very similar to those seen in mixed hot and cold dark matter models.

Hubble induced mass after inflation in spectator field models

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

Fujita, Tomohiro; Harigaya, Keisuke, E-mail: tomofuji@stanford.edu, E-mail: keisukeh@icrr.u-tokyo.ac.jp

2016-12-01

Spectator field models such as the curvaton scenario and the modulated reheating are attractive scenarios for the generation of the cosmic curvature perturbation, as the constraints on inflation models are relaxed. In this paper, we discuss the effect of Hubble induced masses on the dynamics of spectator fields after inflation. We pay particular attention to the Hubble induced mass by the kinetic energy of an oscillating inflaton, which is generically unsuppressed but often overlooked. In the curvaton scenario, the Hubble induced mass relaxes the constraint on the property of the inflaton and the curvaton, such as the reheating temperature andmore » the inflation scale. We comment on the implication of our discussion for baryogenesis in the curvaton scenario. In the modulated reheating, the predictions of models e.g. the non-gaussianity can be considerably altered. Furthermore, we propose a new model of the modulated reheating utilizing the Hubble induced mass which realizes a wide range of the local non-gaussianity parameter.« less

Soft inflation

NASA Technical Reports Server (NTRS)

Berkin, Andrew L.; Maeda, Kei-Ichi; Yokoyama, Junichi

1990-01-01

The cosmology resulting from two coupled scalar fields was studied, one which is either a new inflation or chaotic type inflation, and the other which has an exponentially decaying potential. Such a potential may appear in the conformally transformed frame of generalized Einstein theories like the Jordan-Brans-Dicke theory. The constraints necessary for successful inflation are examined. Conventional GUT models such as SU(5) were found to be compatible with new inflation, while restrictions on the self-coupling constant are significantly loosened for chaotic inflation.

Structural Modeling of a Five-Meter Thin Film Inflatable Antenna/Concentrator

NASA Technical Reports Server (NTRS)

Smalley, Kurt B.; Tinker, Michael L.; Taylor, W. Scott; Brunty, Joseph A. (Technical Monitor)

2002-01-01

Inflatable structures have been the subject of renewed interest in recent years for space applications such as communications antennas, solar thermal propulsion, and space solar power. A major advantage of using inflatable structures in space is their extremely light weight. An obvious second advantage is on-orbit deployability and related space savings in the launch configuration. A recent technology demonstrator flight for inflatable structures was the Inflatable Antenna Experiment (IAE) that was deployed on orbit from the Shuttle Orbiter. Although difficulty was encountered in the inflation/deployment phase, the flight was successful overall and provided valuable experience in the use of such structures. Several papers on static structural analysis of inflated cylinders have been written, describing different techniques such as linear shell theory, and nonlinear and variational methods, but very little work had been done in dynamics of inflatable structures until recent years. In 1988 Leonard indicated that elastic beam bending modes could be utilized in approximating lower-order frequencies of inflatable beams. Main, et al. wrote a very significant 1995 paper describing results of modal tests of inflated cantilever beams and the determination of effective material properties. Changes in material properties for different pressures were also discussed, and the beam model was used in a more complex structure. The paper demonstrated that conventional finite element analysis packages could be very useful in the analysis of complex inflatable structures. The purposes of this paper are to discuss the methodology for dynamically characterizing a large 5-meter thin film inflatable reflector, and to discuss the test arrangement and results. Nonlinear finite element modal results are compared to modal test data. The work is significant and of considerable interest to researchers because of 1) the large size of the structure, making it useful for scaling studies, and 2

Logistic regression for dichotomized counts.

PubMed

Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

2016-12-01

Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

First-order inflation. [in cosmology

NASA Technical Reports Server (NTRS)

Kolb, Edward W.

1991-01-01

In the original proposal, inflation occurred in the process of a strongly first-order phase transition. This model was soon demonstrated to be fatally flawed. Subsequent models for inflation involved phase transitions that were second-order, or perhaps weakly first-order; some even involved no phase transition at all. Recently the possibility of inflation during a strongly first-order phase transition has been revived. In this paper, some models for first-order inflation are discussed, and unique signatures that result if inflation is realized in a first-order transition are emphasized. Some of the history of inflation is reviewed to demonstrate how first-order inflation differs from other models.

Observing the inflation potential. [in models of cosmological inflation

NASA Technical Reports Server (NTRS)

Copeland, Edmund J.; Kolb, Edward W.; Liddle, Andrew R.; Lidsey, James E.

1993-01-01

We show how observations of the density perturbation (scalar) spectrum and the gravitational wave (tensor) spectrum allow a reconstruction of the potential responsible for cosmological inflation. A complete functional reconstruction or a perturbative approximation about a single scale are possible; the suitability of each approach depends on the data available. Consistency equations between the scalar and tensor spectra are derived, which provide a powerful signal of inflation.

Fast or Slow Rescue Ventilations: A Predictive Model of Gastric Inflation.

PubMed

Fitz-Clarke, John R

2018-05-01

Rescue ventilations are given during respiratory and cardiac arrest. Tidal volume must assure oxygen delivery; however, excessive pressure applied to an unprotected airway can cause gastric inflation, regurgitation, and pulmonary aspiration. The optimal technique provides mouth pressure and breath duration that minimize gastric inflation. It remains unclear if breath delivery should be fast or slow, and how inflation time affects the division of gas flow between the lungs and esophagus. A physiological model was used to predict and compare rates of gastric inflation and to determine ideal ventilation duration. Gas flow equations were based on standard pulmonary physiology. Gastric inflation was assumed to occur whenever mouth pressure exceeded lower esophageal sphincter pressure. Mouth pressure profiles that approximated mouth-to-mouth ventilation and bag-valve-mask ventilation were investigated. Target tidal volumes were set to 0.6 and 1.0 L. Compliance and airway resistance were varied. Rapid breaths shorter than 1 s required high mouth pressures, up to 25 cm H 2 O to achieve the target lung volume, which thus promotes gastric inflation. Slow breaths longer than 1 s permitted lower mouth pressures but increased time over which airway pressure exceeded lower esophageal sphincter pressure. The gastric volume increased with breath durations that exceeded 1 s for both mouth pressure profiles. Breath duration of ∼1.0 s caused the least gastric inflation in most scenarios. Very low esophageal sphincter pressure favored a shift toward 0.5 s. High resistance and low compliance each increased gastric inflation and altered ideal breath times. The model illustrated a general theory of optimal rescue ventilation. Breath duration with an unprotected airway should be 1 s to minimize gastric inflation. Short pressure-driven and long duration-driven gastric inflation regimens provide a unifying explanation for results in past studies. Copyright © 2018 by Daedalus Enterprises.

Horizon feedback inflation

NASA Astrophysics Data System (ADS)

Fairbairn, Malcolm; Markkanen, Tommi; Rodriguez Roman, David

2018-04-01

We consider the effect of the Gibbons-Hawking radiation on the inflaton in the situation where it is coupled to a large number of spectator fields. We argue that this will lead to two important effects - a thermal contribution to the potential and a gradual change in parameters in the Lagrangian which results from thermodynamic and energy conservation arguments. We present a scenario of hilltop inflation where the field starts trapped at the origin before slowly experiencing a phase transition during which the field extremely slowly moves towards its zero temperature expectation value. We show that it is possible to obtain enough e-folds of expansion as well as the correct spectrum of perturbations without hugely fine-tuned parameters in the potential (albeit with many spectator fields). We also comment on how initial conditions for inflation can arise naturally in this situation.

Bounce inflation cosmology with Standard Model Higgs boson

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

Wan, Youping; Huang, Fa Peng; Zhang, Xinmin

It is of great interest to connect cosmology in the early universe to the Standard Model of particle physics. In this paper, we try to construct a bounce inflation model with the standard model Higgs boson, where the one loop correction is taken into account in the effective potential of Higgs field. In this model, a Galileon term has been introduced to eliminate the ghost mode when bounce happens. Moreover, due to the fact that the Fermion loop correction can make part of the Higgs potential negative, one naturally obtains a large equation of state(EoS) parameter in the contracting phase,more » which can eliminate the anisotropy problem. After the bounce, the model can drive the universe into the standard higgs inflation phase, which can generate nearly scale-invariant power spectrum.« less

Anisotropic inflation with a non-minimally coupled electromagnetic field to gravity

NASA Astrophysics Data System (ADS)

Adak, Muzaffer; Akarsu, Özgür; Dereli, Tekin; Sert, Özcan

2017-11-01

We consider the non-minimal model of gravity in Y(R) F2-form. We investigate a particular case of the model, for which the higher order derivatives are eliminated but the scalar curvature R is kept to be dynamical via the constraint YRFmnFmn =-2/κ2. The effective fluid obtained can be represented by interacting electromagnetic field and vacuum depending on Y(R), namely, the energy density of the vacuum tracks R while energy density of the conventional electromagnetic field is dynamically scaled with the factor Y(R)/2. We give exact solutions for anisotropic inflation by assuming the volume scale factor of the Universe exhibits a power-law expansion. The directional scale factors do not necessarily exhibit power-law expansion, which would give rise to a constant expansion anisotropy, but expand non-trivially and give rise to a non-monotonically evolving expansion anisotropy that eventually converges to a non-zero constant. Relying on this fact, we discuss the anisotropic e-fold during the inflation by considering observed scale invariance in CMB and demanding the Universe to undergo the same amount of e-folds in all directions. We calculate the residual expansion anisotropy at the end of inflation, though as a result of non-monotonic behaviour of expansion anisotropy all the axes of the Universe undergo the same of amount of e-folds by the end of inflation. We also discuss the generation of the modified electromagnetic field during the first few e-folds of the inflation and its persistence against to the vacuum till end of inflation.

Modulus D-term inflation

NASA Astrophysics Data System (ADS)

Kadota, Kenji; Kobayashi, Tatsuo; Saga, Ikumi; Sumita, Keigo

2018-04-01

We propose a new model of single-field D-term inflation in supergravity, where the inflation is driven by a single modulus field which transforms non-linearly under the U(1) gauge symmetry. One of the notable features of our modulus D-term inflation scenario is that the global U(1) remains unbroken in the vacuum and hence our model is not plagued by the cosmic string problem which can exclude most of the conventional D-term inflation models proposed so far due to the CMB observations.

A novel stent inflation protocol improves long-term outcomes compared with rapid inflation/deflation deployment method.

PubMed

Vallurupalli, Srikanth; Kasula, Srikanth; Kumar Agarwal, Shiv; Pothineni, Naga Venkata K; Abualsuod, Amjad; Hakeem, Abdul; Ahmed, Zubair; Uretsky, Barry F

2017-08-01

High-pressure inflation for coronary stent deployment is universally performed. However, the duration of inflation is variable and does not take into account differences in lesion compliance. We developed a standardized "pressure optimization protocol" (POP) using inflation pressure stability rather than an arbitrary inflation time or angiographic balloon appearance for stent deployment. Whether this approach improves long-term outcomes is unknown. 792 patients who underwent PCI using either rapid inflation/deflation (n = 376) or POP (n = 416) between January 2009 and March 2014 were included. Exclusion criteria included PCI for acute myocardial infarction, in-stent restenosis, chronic total occlusion, left main, and saphenous vein graft lesions. Primary endpoint was target vessel failure [TVF = combined end point of target vessel revascularization (TVR), myocardial infarction, and cardiac death]. Outcomes were analyzed in the entire cohort and in a propensity analysis. Stent implantation using POP with a median follow-up of 1317 days was associated with lower TVF compared with rapid inflation/deflation (10.1 vs. 17.8%, P < 0.0001). This difference was driven by a decrease in TVR (7 vs. 10.6%, P = 0.0016) and cardiac death (2.9 vs. 5.8%, P = 0.017) while there was no difference in myocardial infarction (1 vs. 1.9%, P = 0.19). In the Cox regression model, deployment using POP was the only independent predictor of reduced TVF (HR 0.43; 0.29-0.64; P < 0.0001). In the propensity analysis (330 patients per group) TVF remained lower with POP vs. rapid inflation/deflation (10 vs. 18%, P < 0.0001). Stent deployment using POP led to reduced TVF compared to rapid I/D. These results recommend this method to improve long-term outcomes. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Modeling number of claims and prediction of total claim amount

NASA Astrophysics Data System (ADS)

Acar, Aslıhan Şentürk; Karabey, Uǧur

2017-07-01

In this study we focus on annual number of claims of a private health insurance data set which belongs to a local insurance company in Turkey. In addition to Poisson model and negative binomial model, zero-inflated Poisson model and zero-inflated negative binomial model are used to model the number of claims in order to take into account excess zeros. To investigate the impact of different distributional assumptions for the number of claims on the prediction of total claim amount, predictive performances of candidate models are compared by using root mean square error (RMSE) and mean absolute error (MAE) criteria.

How thermal inflation can save minimal hybrid inflation in supergravity

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

Dimopoulos, Konstantinos; Owen, Charlotte

2016-10-12

Minimal hybrid inflation in supergravity has been ruled out by the 2015 Planck observations because the spectral index of the produced curvature perturbation falls outside observational bounds. To resurrect the model, a number of modifications have been put forward but many of them spoil the accidental cancellation that resolves the η-problem and require complicated Kähler constructions to counterbalance the lost cancellation. In contrast, in this paper the model is rendered viable by supplementing the scenario with a brief period of thermal inflation, which follows the reheating of primordial inflation. The scalar field responsible for thermal inflation requires a large non-zeromore » vacuum expectation value (VEV) and a flat potential. We investigate the VEV of such a flaton field and its subsequent effect on the inflationary observables. We find that, for large VEV, minimal hybrid inflation in supergravity produces a spectral index within the 1-σ Planck bound and a tensor-to-scalar ratio which may be observable in the near future. The mechanism is applicable to other inflationary models.« less

Tax revenue and inflation rate predictions in Banda Aceh using Vector Error Correction Model (VECM)

NASA Astrophysics Data System (ADS)

Maulia, Eva; Miftahuddin; Sofyan, Hizir

2018-05-01

A country has some important parameters to achieve the welfare of the economy, such as tax revenues and inflation. One of the largest revenues of the state budget in Indonesia comes from the tax sector. Besides, the rate of inflation occurring in a country can be used as one measure, to measure economic problems that the country facing. Given the importance of tax revenue and inflation rate control in achieving economic prosperity, it is necessary to analyze the relationship and forecasting tax revenue and inflation rate. VECM (Vector Error Correction Model) was chosen as the method used in this research, because of the data used in the form of multivariate time series data. This study aims to produce a VECM model with optimal lag and to predict the tax revenue and inflation rate of the VECM model. The results show that the best model for data of tax revenue and the inflation rate in Banda Aceh City is VECM with 3rd optimal lag or VECM (3). Of the seven models formed, there is a significant model that is the acceptance model of income tax. The predicted results of tax revenue and the inflation rate in Kota Banda Aceh for the next 6, 12 and 24 periods (months) obtained using VECM (3) are considered valid, since they have a minimum error value compared to other models.

Inflation from Minkowski space

DOE PAGES

Pirtskhalava, David; Santoni, Luca; Trincherini, Enrico; ...

2014-12-23

Here, we propose a class of scalar models that, once coupled to gravity, lead to cosmologies that smoothly and stably connect an inflationary quasi-de Sitter universe to a low, or even zero-curvature, maximally symmetric spacetime in the asymptotic past, strongly violating the null energy condition (H • >>H2) at intermediate times. The models are deformations of the conformal galileon lagrangian and are therefore based on symmetries, both exact and approximate, that ensure the quantum robustness of the whole picture. The resulting cosmological backgrounds can be viewed as regularized extensions of the galilean genesis scenario, or, equivalently, as ‘early-time-complete’ realizations ofmore » inflation. The late-time inflationary dynamics possesses phenomenologically interesting properties: it can produce a large tensor-to-scalar ratio within the regime of validity of the effective field theory and can lead to sizeable equilateral nongaussianities.« less

Microwave background anisotropies in quasiopen inflation

NASA Astrophysics Data System (ADS)

García-Bellido, Juan; Garriga, Jaume; Montes, Xavier

1999-10-01

Quasiopenness seems to be generic to multifield models of single-bubble open inflation. Instead of producing infinite open universes, these models actually produce an ensemble of very large but finite inflating islands. In this paper we study the possible constraints from CMB anisotropies on existing models of open inflation. The effect of supercurvature anisotropies combined with the quasiopenness of the inflating regions make some models incompatible with observations, and severely reduces the parameter space of others. Supernatural open inflation and the uncoupled two-field model seem to be ruled out due to these constraints for values of Ω0<~0.98. Others, such as the open hybrid inflation model with suitable parameters for the slow roll potential can be made compatible with observations.

Simple cosmological model with inflation and late times acceleration

NASA Astrophysics Data System (ADS)

Szydłowski, Marek; Stachowski, Aleksander

2018-03-01

In the framework of polynomial Palatini cosmology, we investigate a simple cosmological homogeneous and isotropic model with matter in the Einstein frame. We show that in this model during cosmic evolution, early inflation appears and the accelerating phase of the expansion for the late times. In this frame we obtain the Friedmann equation with matter and dark energy in the form of a scalar field with a potential whose form is determined in a covariant way by the Ricci scalar of the FRW metric. The energy density of matter and dark energy are also parameterized through the Ricci scalar. Early inflation is obtained only for an infinitesimally small fraction of energy density of matter. Between the matter and dark energy, there exists an interaction because the dark energy is decaying. For the characterization of inflation we calculate the slow roll parameters and the constant roll parameter in terms of the Ricci scalar. We have found a characteristic behavior of the time dependence of density of dark energy on the cosmic time following the logistic-like curve which interpolates two almost constant value phases. From the required numbers of N-folds we have found a bound on the model parameter.

A zero-augmented generalized gamma regression calibration to adjust for covariate measurement error: A case of an episodically consumed dietary intake

PubMed Central

Agogo, George O.

2017-01-01

Measurement error in exposure variables is a serious impediment in epidemiological studies that relate exposures to health outcomes. In nutritional studies, interest could be in the association between long-term dietary intake and disease occurrence. Long-term intake is usually assessed with food frequency questionnaire (FFQ), which is prone to recall bias. Measurement error in FFQ-reported intakes leads to bias in parameter estimate that quantifies the association. To adjust for bias in the association, a calibration study is required to obtain unbiased intake measurements using a short-term instrument such as 24-hour recall (24HR). The 24HR intakes are used as response in regression calibration to adjust for bias in the association. For foods not consumed daily, 24HR-reported intakes are usually characterized by excess zeroes, right skewness, and heteroscedasticity posing serious challenge in regression calibration modeling. We proposed a zero-augmented calibration model to adjust for measurement error in reported intake, while handling excess zeroes, skewness, and heteroscedasticity simultaneously without transforming 24HR intake values. We compared the proposed calibration method with the standard method and with methods that ignore measurement error by estimating long-term intake with 24HR and FFQ-reported intakes. The comparison was done in real and simulated datasets. With the 24HR, the mean increase in mercury level per ounce fish intake was about 0.4; with the FFQ intake, the increase was about 1.2. With both calibration methods, the mean increase was about 2.0. Similar trend was observed in the simulation study. In conclusion, the proposed calibration method performs at least as good as the standard method. PMID:27704599

Censored Hurdle Negative Binomial Regression (Case Study: Neonatorum Tetanus Case in Indonesia)

NASA Astrophysics Data System (ADS)

Yuli Rusdiana, Riza; Zain, Ismaini; Wulan Purnami, Santi

2017-06-01

Hurdle negative binomial model regression is a method that can be used for discreate dependent variable, excess zero and under- and overdispersion. It uses two parts approach. The first part estimates zero elements from dependent variable is zero hurdle model and the second part estimates not zero elements (non-negative integer) from dependent variable is called truncated negative binomial models. The discrete dependent variable in such cases is censored for some values. The type of censor that will be studied in this research is right censored. This study aims to obtain the parameter estimator hurdle negative binomial regression for right censored dependent variable. In the assessment of parameter estimation methods used Maximum Likelihood Estimator (MLE). Hurdle negative binomial model regression for right censored dependent variable is applied on the number of neonatorum tetanus cases in Indonesia. The type data is count data which contains zero values in some observations and other variety value. This study also aims to obtain the parameter estimator and test statistic censored hurdle negative binomial model. Based on the regression results, the factors that influence neonatorum tetanus case in Indonesia is the percentage of baby health care coverage and neonatal visits.

Gravitational waves from warm inflation

NASA Astrophysics Data System (ADS)

Li, Xi-Bin; Wang, He; Zhu, Jian-Yang

2018-03-01

A fundamental prediction of inflation is a nearly scale-invariant spectrum of gravitational wave. The features of such a signal provide extremely important information about the physics of the early universe. In this paper, we focus on several topics about warm inflation. First, we discuss the stability property about warm inflation based on nonequilibrium statistical mechanics, which gives more fundamental physical illustrations to thermal property of such model. Then, we calculate the power spectrum of gravitational waves generated during warm inflation, in which there are three components contributing to such spectrum: thermal term, quantum term, and cross term combining the both. We also discuss some interesting properties about these terms and illustrate them in different panels. As a model different from cold inflation, warm inflation model has its individual properties in observational practice, so we finally give a discussion about the observational effect to distinguish it from cold inflation.

Unemployment and inflation dynamics prior to the economic downturn of 2007-2008.

PubMed

Guastello, Stephen J; Myers, Adam

2009-10-01

This article revisits a long-standing theoretical issue as to whether a "natural rate" of unemployment exists in the sense of an exogenously driven fixed-point Walrasian equilibrium or attractor, or whether more complex dynamics such as hysteresis or chaos characterize an endogenous dynamical process instead. The same questions are posed regarding a possible natural rate of inflation along with an investigation of the actual relationship between inflation and unemployment for which extent theories differ. Time series of unemployment and inflation for US data - were analyzed using the exponential model series and nonlinear regression for capturing Lyapunov exponents and transfer effects from other variables. The best explanation for unemployment was that it is a chaotic variable that is driven in part by inflation. The best explanation for inflation is that it is also a chaotic variable driven in part by unemployment and the prices of treasury bills. Estimates of attractors' epicenters were calculated in lieu of classical natural rates.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Mutated hilltop inflation revisited

NASA Astrophysics Data System (ADS)

Pal, Barun Kumar

2018-05-01

In this work we re-investigate pros and cons of mutated hilltop inflation. Applying Hamilton-Jacobi formalism we solve inflationary dynamics and find that inflation goes on along the {W}_{-1} branch of the Lambert function. Depending on the model parameter mutated hilltop model renders two types of inflationary solutions: one corresponds to small inflaton excursion during observable inflation and the other describes large field inflation. The inflationary observables from curvature perturbation are in tune with the current data for a wide range of the model parameter. The small field branch predicts negligible amount of tensor to scalar ratio r˜ O(10^{-4}), while the large field sector is capable of generating high amplitude for tensor perturbations, r˜ O(10^{-1}). Also, the spectral index is almost independent of the model parameter along with a very small negative amount of scalar running. Finally we find that the mutated hilltop inflation closely resembles the α -attractor class of inflationary models in the limit of α φ ≫ 1.

Inflation at the electroweak scale

NASA Technical Reports Server (NTRS)

Knox, Lloyd; Turner, Michael S.

1993-01-01

We present a model for slow-rollover inflation where the vacuum energy that drives inflation is of the order of G(F) exp -2; unlike most models, the conversion of vacuum energy to radiation ('reheating') is moderately efficient. The scalar field responsible for inflation is a standard-model singlet, develops a vacuum expectation value of 4 x 10 exp 6 GeV, has a mass of about 1 GeV, and can play a role in electroweak phenomena. We also discuss models where the energy scale of inflation is somewhat larger, but still well below the unification scale.

Modelling inflation in transportation, comunication and financial services using B-Spline time series model

NASA Astrophysics Data System (ADS)

Suparti; Prahutama, Alan; Santoso, Rukun

2018-05-01

Inflation is an increase in the price of goods and services in general where the goods and services are the basic needs of society or the decline of the selling power of a country’s currency. Significant inflationary increases occurred in 2013. This increase was contributed by a significant increase in some inflation sectors / groups i.e transportation, communication and financial services; the foodstuff sector, and the housing, water, electricity, gas and fuel sectors. However, significant contributions occurred in the transportation, communications and financial services sectors. In the model of IFIs in the transportation, communication and financial services sector use the B-Spline time series approach, where the predictor variable is Yt, whereas the predictor is a significant lag (in this case Yt-1). In modeling B-spline time series determined the order and the optimum knot point. Optimum knot determination using Generalized Cross Validation (GCV). In inflation modeling for transportation sector, communication and financial services obtained model of B-spline order 2 with 2 points knots produce MAPE less than 50%.

Parametric regression model for survival data: Weibull regression model as an example

PubMed Central

2016-01-01

Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model. To make clinical investigators familiar with Weibull regression model, this article introduces some basic knowledge on Weibull regression model and then illustrates how to fit the model with R software. The SurvRegCensCov package is useful in converting estimated coefficients to clinical relevant statistics such as hazard ratio (HR) and event time ratio (ETR). Model adequacy can be assessed by inspecting Kaplan-Meier curves stratified by categorical variable. The eha package provides an alternative method to model Weibull regression model. The check.dist() function helps to assess goodness-of-fit of the model. Variable selection is based on the importance of a covariate, which can be tested using anova() function. Alternatively, backward elimination starting from a full model is an efficient way for model development. Visualization of Weibull regression model after model development is interesting that it provides another way to report your findings. PMID:28149846

Starobinsky-like inflation and neutrino masses in a no-scale SO(10) model

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

Ellis, John; Theoretical Physics Department, CERN,CH-1211 Geneva 23; Garcia, Marcos A.G.

2016-11-08

Using a no-scale supergravity framework, we construct an SO(10) model that makes predictions for cosmic microwave background observables similar to those of the Starobinsky model of inflation, and incorporates a double-seesaw model for neutrino masses consistent with oscillation experiments and late-time cosmology. We pay particular attention to the behaviour of the scalar fields during inflation and the subsequent reheating.

Modeling Inflation Using a Non-Equilibrium Equation of Exchange

NASA Technical Reports Server (NTRS)

Chamberlain, Robert G.

2013-01-01

Inflation is a change in the prices of goods that takes place without changes in the actual values of those goods. The Equation of Exchange, formulated clearly in a seminal paper by Irving Fisher in 1911, establishes an equilibrium relationship between the price index P (also known as "inflation"), the economy's aggregate output Q (also known as "the real gross domestic product"), the amount of money available for spending M (also known as "the money supply"), and the rate at which money is reused V (also known as "the velocity of circulation of money"). This paper offers first a qualitative discussion of what can cause these factors to change and how those causes might be controlled, then develops a quantitative model of inflation based on a non-equilibrium version of the Equation of Exchange. Causal relationships are different from equations in that the effects of changes in the causal variables take time to play out-often significant amounts of time. In the model described here, wages track prices, but only after a distributed lag. Prices change whenever the money supply, aggregate output, or the velocity of circulation of money change, but only after a distributed lag. Similarly, the money supply depends on the supplies of domestic and foreign money, which depend on the monetary base and a variety of foreign transactions, respectively. The spreading of delays mitigates the shocks of sudden changes to important inputs, but the most important aspect of this model is that delays, which often have dramatic consequences in dynamic systems, are explicitly incorporated.macroeconomics, inflation, equation of exchange, non-equilibrium, Athena Project

Soft inflation. [in cosmology

NASA Technical Reports Server (NTRS)

Berkin, Andrew L.; Maeda, Kei-Ichi; Yokoyama, Jun'ichi

1990-01-01

The cosmology resulting from two coupled scalar fields was studied, one which is either a new inflation or chaotic type inflation, and the other which has an exponentially decaying potential. Such a potential may appear in the conformally transformed frame of generalized Einstein theories like the Jordan-Brans-Dicke theory. The constraints necessary for successful inflation are examined. Conventional GUT models such as SU(5) were found to be compatible with new inflation, while restrictions on the self-coupling constant are significantly loosened for chaotic inflation.

Kähler-driven tribrid inflation

NASA Astrophysics Data System (ADS)

Antusch, Stefan; Nolde, David

2012-11-01

We discuss a new class of tribrid inflation models in supergravity, where the shape of the inflaton potential is dominated by effects from the Kähler potential. Tribrid inflation is a variant of hybrid inflation which is particularly suited for connecting inflation with particle physics, since the inflaton can be a D-flat combination of charged fields from the matter sector. In models of tribrid inflation studied so far, the inflaton potential was dominated by either loop corrections or by mixing effects with the waterfall field (as in "pseudosmooth" tribrid inflation). Here we investigate the third possibility, namely that tribrid inflation is dominantly driven by effects from higher-dimensional operators of the Kähler potential. We specify for which superpotential parameters the new regime is realized and show how it can be experimentally distinguished from the other two (loop-driven and "pseudosmooth") regimes.

Modeling of Aerobrake Ballute Stagnation Point Temperature and Heat Transfer to Inflation Gas

NASA Technical Reports Server (NTRS)

Bahrami, Parviz A.

2012-01-01

A trailing Ballute drag device concept for spacecraft aerocapture is considered. A thermal model for calculation of the Ballute membrane temperature and the inflation gas temperature is developed. An algorithm capturing the most salient features of the concept is implemented. In conjunction with the thermal model, trajectory calculations for two candidate missions, Titan Explorer and Neptune Orbiter missions, are used to estimate the stagnation point temperature and the inflation gas temperature. Radiation from both sides of the membrane at the stagnation point and conduction to the inflating gas is included. The results showed that the radiation from the membrane and to a much lesser extent conduction to the inflating gas, are likely to be the controlling heat transfer mechanisms and that the increase in gas temperature due to aerodynamic heating is of secondary importance.

No-scale inflation

NASA Astrophysics Data System (ADS)

Ellis, John; Garcia, Marcos A. G.; Nanopoulos, Dimitri V.; Olive, Keith A.

2016-05-01

Supersymmetry is the most natural framework for physics above the TeV scale, and the corresponding framework for early-Universe cosmology, including inflation, is supergravity. No-scale supergravity emerges from generic string compactifications and yields a non-negative potential, and is therefore a plausible framework for constructing models of inflation. No-scale inflation yields naturally predictions similar to those of the Starobinsky model based on R+{R}2 gravity, with a tilted spectrum of scalar perturbations: {n}s∼ 0.96, and small values of the tensor-to-scalar perturbation ratio r\\lt 0.1, as favoured by Planck and other data on the cosmic microwave background (CMB). Detailed measurements of the CMB may provide insights into the embedding of inflation within string theory as well as its links to collider physics.

Gauge fields and inflation

NASA Astrophysics Data System (ADS)

Maleknejad, A.; Sheikh-Jabbari, M. M.; Soda, J.

2013-07-01

The isotropy and homogeneity of the cosmic microwave background (CMB) favors “scalar driven” early Universe inflationary models. However, gauge fields and other non-scalar fields are far more common at all energy scales, in particular at high energies seemingly relevant to inflation models. Hence, in this review we consider the role and consequences, theoretical and observational, that gauge fields can have during the inflationary era. Gauge fields may be turned on in the background during inflation, or may become relevant at the level of cosmic perturbations. There have been two main classes of models with gauge fields in the background, models which show violation of the cosmic no-hair theorem and those which lead to isotropic FLRW cosmology, respecting the cosmic no-hair theorem. Models in which gauge fields are only turned on at the cosmic perturbation level, may source primordial magnetic fields. We also review specific observational features of these models on the CMB and/or the primordial cosmic magnetic fields. Our discussions will be mainly focused on the inflation period, with only a brief discussion on the post inflationary (p)reheating era. Large field models: The initial value of the inflaton field is large, generically super-Planckian, and it rolls slowly down toward the potential minimum at smaller φ values. For instance, chaotic inflation is one of the representative models of this class. The typical potential of large-field models has a monomial form as V(φ)=V0φn. A simple analysis using the dynamical equations reveals that for number of e-folds Ne larger than 60, we require super-Planckian initial field values,5φ0>3M. For these models typically ɛ˜η˜Ne-1. Small field models: Inflaton field is initially small and slowly evolves toward the potential minimum at larger φ values. The small field models are characterized by the following potential V(φ)=V0(1-(), which corresponds to a Taylor expansion about the origin, but more realistic

Selecting the right statistical model for analysis of insect count data by using information theoretic measures.

PubMed

Sileshi, G

2006-10-01

Researchers and regulatory agencies often make statistical inferences from insect count data using modelling approaches that assume homogeneous variance. Such models do not allow for formal appraisal of variability which in its different forms is the subject of interest in ecology. Therefore, the objectives of this paper were to (i) compare models suitable for handling variance heterogeneity and (ii) select optimal models to ensure valid statistical inferences from insect count data. The log-normal, standard Poisson, Poisson corrected for overdispersion, zero-inflated Poisson, the negative binomial distribution and zero-inflated negative binomial models were compared using six count datasets on foliage-dwelling insects and five families of soil-dwelling insects. Akaike's and Schwarz Bayesian information criteria were used for comparing the various models. Over 50% of the counts were zeros even in locally abundant species such as Ootheca bennigseni Weise, Mesoplatys ochroptera Stål and Diaecoderus spp. The Poisson model after correction for overdispersion and the standard negative binomial distribution model provided better description of the probability distribution of seven out of the 11 insects than the log-normal, standard Poisson, zero-inflated Poisson or zero-inflated negative binomial models. It is concluded that excess zeros and variance heterogeneity are common data phenomena in insect counts. If not properly modelled, these properties can invalidate the normal distribution assumptions resulting in biased estimation of ecological effects and jeopardizing the integrity of the scientific inferences. Therefore, it is recommended that statistical models appropriate for handling these data properties be selected using objective criteria to ensure efficient statistical inference.

First-order inflation. [in cosmology

NASA Technical Reports Server (NTRS)

Turner, Michael S.

1992-01-01

I discuss the most recent model of inflation. In first-order inflation the inflationary epoch is associated with a first-order phase transition, with the most likely candidate being GUT symmetry breaking. The transition from the false-vacuum inflationary phase to the true-vacuum radiation-dominated phase proceeds through the nucleation and percolation of true-vacuum bubbles. The first successful and simplest model of first-order inflation, extended inflation, is discussed in some detail: evolution of the cosmic-scale factor, reheating, density perturbations, and the production of gravitational waves both from quantum fluctuations and bubble collisions. Particular attention is paid to the most critical issue in any model of first-order inflation: the requirements on the nucleation rate to ensure a graceful transition from the inflationary phase to the radiation-dominated phase.

Analysis of aggregate impact factor inflation in ophthalmology.

PubMed

Caramoy, Albert; Korwitz, Ulrich; Eppelin, Anita; Kirchhof, Bernd; Fauser, Sascha

2013-01-01

To analyze the aggregate impact factor (AIF) in ophthalmology, its inflation rate, and its relation to other subject fields. A retrospective, database review of all subject fields in the Journal Citation Reports (JCR), Science edition. Citation data, AIF, number of journals and citations from the years 2003-2011 were analyzed. Data were retrieved from JCR. Future trends were calculated using a linear regression method. The AIF varies considerably between subjects. It shows also an inflation rate, which varies annually. The AIF inflation rate in ophthalmology was not as high as the background AIF inflation rate. The AIF inflation rate caused the AIF to increase annually. Not considering these variations in the AIF between years and between fields will make the AIF as a bibliometric tool inappropriate. Copyright © 2012 S. Karger AG, Basel.

Topological inflation with graceful exit

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

Marunović, Anja; Prokopec, Tomislav, E-mail: a.marunovic@uu.nl, E-mail: t.prokopec@uu.nl

We investigate a class of models of topological inflation in which a super-Hubble-sized global monopole seeds inflation. These models are attractive since inflation starts from rather generic initial conditions, but their not so attractive feature is that, unless symmetry is again restored, inflation never ends. In this work we show that, in presence of another nonminimally coupled scalar field, that is both quadratically and quartically coupled to the Ricci scalar, inflation naturally ends, representing an elegant solution to the graceful exit problem of topological inflation. While the monopole core grows during inflation, the growth stops after inflation, such that themore » monopole eventually enters the Hubble radius, and shrinks to its Minkowski space size, rendering it immaterial for the subsequent Universe's dynamics. Furthermore, we find that our model can produce cosmological perturbations that source CMB temperature fluctuations and seed large scale structure statistically consistent (within one standard deviation) with all available data. In particular, for small and (in our convention) negative nonminimal couplings, the scalar spectral index can be as large as n {sub s} ≅ 0.955, which is about one standard deviation lower than the central value quoted by the most recent Planck Collaboration.« less

Accidental inflation from Kähler uplifting

NASA Astrophysics Data System (ADS)

Ben-Dayan, Ido; Jing, Shenglin; Westphal, Alexander; Wieck, Clemens

2014-03-01

We analyze the possibility of realizing inflation with a subsequent dS vacuum in the Käahler uplifting scenario. The inclusion of several quantum corrections to the 4d effective action evades previous no-go theorems and allows for construction of simple and successful models of string inflation. The predictions of several benchmark models are in accord with current observations, i.e., a red spectral index, negligible non-gaussianity, and spectral distortions similar to the simplest models of inflation. A particularly interesting subclass of models are ``left-rolling" ones, where the overall volume of the compactified dimensions shrinks during inflation. We call this phenomenon ``inflation by deflation" (IBD), where deflation refers to the internal manifold. This subclass has the appealing features of being insensitive to initial conditions, avoiding the overshooting problem, and allowing for observable running α ~ 0.012 and enhanced tensor-to-scalar ratio r ~ 10-5. The latter results differ significantly from many string inflation models.

Planck limits on non-canonical generalizations of large-field inflation models

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

Stein, Nina K.; Kinney, William H., E-mail: ninastei@buffalo.edu, E-mail: whkinney@buffalo.edu

2017-04-01

In this paper, we consider two case examples of Dirac-Born-Infeld (DBI) generalizations of canonical large-field inflation models, characterized by a reduced sound speed, c {sub S} < 1. The reduced speed of sound lowers the tensor-scalar ratio, improving the fit of the models to the data, but increases the equilateral-mode non-Gaussianity, f {sup equil.}{sub NL}, which the latest results from the Planck satellite constrain by a new upper bound. We examine constraints on these models in light of the most recent Planck and BICEP/Keck results, and find that they have a greatly decreased window of viability. The upper bound onmore » f {sup equil.}{sub NL} corresponds to a lower bound on the sound speed and a corresponding lower bound on the tensor-scalar ratio of r ∼ 0.01, so that near-future Cosmic Microwave Background observations may be capable of ruling out entire classes of DBI inflation models. The result is, however, not universal: infrared-type DBI inflation models, where the speed of sound increases with time, are not subject to the bound.« less

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2011 CFR

2011-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST... Inspections § 131.580 Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced...

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2010 CFR

2010-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST... Inspections § 131.580 Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced...

Structure analysis of tax revenue and inflation rate in Banda Aceh using vector error correction model with multiple alpha

NASA Astrophysics Data System (ADS)

Sofyan, Hizir; Maulia, Eva; Miftahuddin

2017-11-01

A country has several important parameters to achieve economic prosperity, such as tax revenue and inflation rate. One of the largest revenues of the State Budget in Indonesia comes from the tax sector. Meanwhile, the rate of inflation occurring in a country can be used as an indicator, to measure the good and bad economic problems faced by the country. Given the importance of tax revenue and inflation rate control in achieving economic prosperity, it is necessary to analyze the structure of tax revenue relations and inflation rate. This study aims to produce the best VECM (Vector Error Correction Model) with optimal lag using various alpha and perform structural analysis using the Impulse Response Function (IRF) of the VECM models to examine the relationship of tax revenue, and inflation in Banda Aceh. The results showed that the best model for the data of tax revenue and inflation rate in Banda Aceh City using alpha 0.01 is VECM with optimal lag 2, while the best model for data of tax revenue and inflation rate in Banda Aceh City using alpha 0.05 and 0,1 VECM with optimal lag 3. However, the VECM model with alpha 0.01 yielded four significant models of income tax model, inflation rate of Banda Aceh, inflation rate of health and inflation rate of education in Banda Aceh. While the VECM model with alpha 0.05 and 0.1 yielded one significant model that is income tax model. Based on the VECM models, then there are two structural analysis IRF which is formed to look at the relationship of tax revenue, and inflation in Banda Aceh, the IRF with VECM (2) and IRF with VECM (3).

Measurement error in epidemiologic studies of air pollution based on land-use regression models.

PubMed

Basagaña, Xavier; Aguilera, Inmaculada; Rivera, Marcela; Agis, David; Foraster, Maria; Marrugat, Jaume; Elosua, Roberto; Künzli, Nino

2013-10-15

Land-use regression (LUR) models are increasingly used to estimate air pollution exposure in epidemiologic studies. These models use air pollution measurements taken at a small set of locations and modeling based on geographical covariates for which data are available at all study participant locations. The process of LUR model development commonly includes a variable selection procedure. When LUR model predictions are used as explanatory variables in a model for a health outcome, measurement error can lead to bias of the regression coefficients and to inflation of their variance. In previous studies dealing with spatial predictions of air pollution, bias was shown to be small while most of the effect of measurement error was on the variance. In this study, we show that in realistic cases where LUR models are applied to health data, bias in health-effect estimates can be substantial. This bias depends on the number of air pollution measurement sites, the number of available predictors for model selection, and the amount of explainable variability in the true exposure. These results should be taken into account when interpreting health effects from studies that used LUR models.

A new model for CD8+ T cell memory inflation based upon a recombinant adenoviral vector1

PubMed Central

Bolinger, Beatrice; Sims, Stuart; O’Hara, Geraldine; de Lara, Catherine; Tchilian, Elma; Firner, Sonja; Engeler, Daniel; Ludewig, Burkhard; Klenerman, Paul

2013-01-01

CD8+ T cell memory inflation, first described in murine cytomegalovirus (MCMV) infection, is characterized by the accumulation of high-frequency, functional antigen-specific CD8+ T cell pools with an effector-memory phenotype and enrichment in peripheral organs. Although persistence of antigen is considered essential, the rules underpinning memory inflation are still unclear. The MCMV model is, however, complicated by the virus’s low-level persistence, and stochastic reactivation. We developed a new model of memory inflation based upon a βgal-recombinant adenovirus vector (Ad-LacZ). After i.v. administration in C57BL/6 mice we observe marked memory inflation in the βgal96 epitope, while a second epitope, βgal497, undergoes classical memory formation. The inflationary T cell responses show kinetics, distribution, phenotype and functions similar to those seen in MCMV and are reproduced using alternative routes of administration. Memory inflation in this model is dependent on MHC Class II. As in MCMV, only the inflating epitope showed immunoproteasome-independence. These data define a new model for memory inflation, which is fully replication-independent, internally controlled and reproduces the key immunologic features of the CD8+ T cell response. This model provides insight into the mechanisms responsible for memory inflation, and since it is based on a vaccine vector, also is relevant to novel T cell-inducing vaccines in humans. PMID:23509359

Modular invariant inflation

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

Kobayashi, Tatsuo; Nitta, Daisuke; Urakawa, Yuko

2016-08-08

Modular invariance is a striking symmetry in string theory, which may keep stringy corrections under control. In this paper, we investigate a phenomenological consequence of the modular invariance, assuming that this symmetry is preserved as well as in a four dimensional (4D) low energy effective field theory. As a concrete setup, we consider a modulus field T whose contribution in the 4D effective field theory remains invariant under the modular transformation and study inflation drived by T. The modular invariance restricts a possible form of the scalar potenntial. As a result, large field models of inflation are hardly realized. Meanwhile,more » a small field model of inflation can be still accomodated in this restricted setup. The scalar potential traced during the slow-roll inflation mimics the hilltop potential V{sub ht}, but it also has a non-negligible deviation from V{sub ht}. Detecting the primordial gravitational waves predicted in this model is rather challenging. Yet, we argue that it may be still possible to falsify this model by combining the information in the reheating process which can be determined self-completely in this setup.« less

Quantum fluctuations and CMB anisotropies in one-bubble open inflation models

NASA Astrophysics Data System (ADS)

Yamamoto, Kazuhiro; Sasaki, Misao; Tanaka, Takahiro

1996-10-01

We first develop a method to calculate a complete set of mode functions that describe the quantum fluctuations generated in one-bubble open inflation models. We consider two classes of models. One is a single scalar field model proposed by Bucher, Goldhaber, and Turok and by us as an example of the open inflation scenario, and the other is a two-field model such as the ``supernatural'' inflation proposed by Linde and Mezhlumian. In both cases we assume the difference in the vacuum energy density between inside and outside the bubble is negligible. There are two kinds of mode functions. One kind has the usual continuous spectrum and the other has a discrete spectrum with characteristic wavelengths exceeding the spatial curvature scale. The latter can be further divided into two classes in terms of its origin. One is called the de Sitter supercurvature mode, which arises due to the global spacetime structure of de Sitter space, and the other is due to fluctuations of the bubble wall. We calculate the spectrum of quantum fluctuations in these models and evaluate the resulting large angular scale CMB anisotropies. We find there are ranges of model parameters that are consistent with observed CMB anisotropies.

Testing Cosmic Inflation

NASA Technical Reports Server (NTRS)

Chuss, David

2010-01-01

The Cosmic Microwave Background (CMB) has provided a wealth of information about the history and physics of the early Universe. Much progress has been made on uncovering the emerging Standard Model of Cosmology by such experiments as COBE and WMAP, and ESA's Planck Surveyor will likely increase our knowledge even more. Despite the success of this model, mysteries remain. Currently understood physics does not offer a compelling explanation for the homogeneity, flatness, and the origin of structure in the Universe. Cosmic Inflation, a brief epoch of exponential expansion, has been posted to explain these observations. If inflation is a reality, it is expected to produce a background spectrum of gravitational waves that will leave a small polarized imprint on the CMB. Discovery of this signal would give the first direct evidence for inflation and provide a window into physics at scales beyond those accessible to terrestrial particle accelerators. I will briefly review aspects of the Standard Model of Cosmology and discuss our current efforts to design and deploy experiments to measure the polarization of the CMB with the precision required to test inflation.

k-essence model of inflation, dark matter, and dark energy

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

Bose, Nilok; Majumdar, A. S.

We investigate the possibility for k-essence dynamics to reproduce the primary features of inflation in the early universe, generate dark matter subsequently, and finally account for the presently observed acceleration. We first show that for a purely kinetic k-essence model the late-time energy density of the universe when expressed simply as a sum of a cosmological constant and a dark matter term leads to a static universe. We then study another k-essence model in which the Lagrangian contains a potential for the scalar field as well as a noncanonical kinetic term. We show that such a model generates the basicmore » features of inflation in the early universe, and also gives rise to dark matter and dark energy at appropriate subsequent stages. Observational constraints on the parameters of this model are obtained.« less

Inflection-point inflation in a hyper-charge oriented U ( 1 ) X model

DOE PAGES

Okada, Nobuchika; Okada, Satomi; Raut, Digesh

2017-03-31

Inflection-point inflation is an interesting possibility to realize a successful slow-roll inflation when inflation is driven by a single scalar field with its value during inflation below the Planck mass (ΦI≲M Pl). In order for a renormalization group (RG) improved effective λΦ 4 potential to develop an inflection-point, the running quartic coupling λ(Φ) must exhibit a minimum with an almost vanishing value in its RG evolution, namely λ(Φ I)≃0 and β λ(ΦI)≃0, where β λ is the beta-function of the quartic coupling. Here in this paper, we consider the inflection-point inflation in the context of the minimal gauged U(1) Xmore » extended Standard Model (SM), which is a generalization of the minimal U(1) B$-$L model, and is constructed as a linear combination of the SM U(1) Y and U(1) B$-$L gauge symmetries. We identify the U(1) X Higgs field with the inflaton field. For a successful inflection-point inflation to be consistent with the current cosmological observations, the mass ratios among the U(1) X gauge boson, the right-handed neutrinos and the U(1) X Higgs boson are fixed. Focusing on the case that the extra U(1) X gauge symmetry is mostly aligned along the SM U(1) Y direction, we investigate a consistency between the inflationary predictions and the latest LHC Run-2 results on the search for a narrow resonance with the di-lepton final state.« less

Inflection-point inflation in a hyper-charge oriented U ( 1 ) X model

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

Okada, Nobuchika; Okada, Satomi; Raut, Digesh

Inflection-point inflation is an interesting possibility to realize a successful slow-roll inflation when inflation is driven by a single scalar field with its value during inflation below the Planck mass (ΦI≲M Pl). In order for a renormalization group (RG) improved effective λΦ 4 potential to develop an inflection-point, the running quartic coupling λ(Φ) must exhibit a minimum with an almost vanishing value in its RG evolution, namely λ(Φ I)≃0 and β λ(ΦI)≃0, where β λ is the beta-function of the quartic coupling. Here in this paper, we consider the inflection-point inflation in the context of the minimal gauged U(1) Xmore » extended Standard Model (SM), which is a generalization of the minimal U(1) B$-$L model, and is constructed as a linear combination of the SM U(1) Y and U(1) B$-$L gauge symmetries. We identify the U(1) X Higgs field with the inflaton field. For a successful inflection-point inflation to be consistent with the current cosmological observations, the mass ratios among the U(1) X gauge boson, the right-handed neutrinos and the U(1) X Higgs boson are fixed. Focusing on the case that the extra U(1) X gauge symmetry is mostly aligned along the SM U(1) Y direction, we investigate a consistency between the inflationary predictions and the latest LHC Run-2 results on the search for a narrow resonance with the di-lepton final state.« less

Accidental inflation from Kähler uplifting

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

Ben-Dayan, Ido; Westphal, Alexander; Wieck, Clemens

2014-03-01

We analyze the possibility of realizing inflation with a subsequent dS vacuum in the Käahler uplifting scenario. The inclusion of several quantum corrections to the 4d effective action evades previous no-go theorems and allows for construction of simple and successful models of string inflation. The predictions of several benchmark models are in accord with current observations, i.e., a red spectral index, negligible non-gaussianity, and spectral distortions similar to the simplest models of inflation. A particularly interesting subclass of models are ''left-rolling'' ones, where the overall volume of the compactified dimensions shrinks during inflation. We call this phenomenon ''inflation by deflation''more » (IBD), where deflation refers to the internal manifold. This subclass has the appealing features of being insensitive to initial conditions, avoiding the overshooting problem, and allowing for observable running α ∼ 0.012 and enhanced tensor-to-scalar ratio r ∼ 10{sup −5}. The latter results differ significantly from many string inflation models.« less

Primordial black holes from single field models of inflation

NASA Astrophysics Data System (ADS)

García-Bellido, Juan; Ruiz Morales, Ester

2017-12-01

Primordial black holes (PBH) have been shown to arise from high peaks in the matter power spectra of multi-field models of inflation. Here we show, with a simple toy model, that it is also possible to generate a peak in the curvature power spectrum of single-field inflation. We assume that the effective dynamics of the inflaton field presents a near-inflection point which slows down the field right before the end of inflation and gives rise to a prominent spike in the fluctuation power spectrum at scales much smaller than those probed by Cosmic Microwave Background (CMB) and Large Scale Structure (LSS) observations. This peak will give rise, upon reentry during the radiation era, to PBH via gravitational collapse. The mass and abundance of these PBH is such that they could constitute the totality of the Dark Matter today. We satisfy all CMB and LSS constraints and predict a very broad range of PBH masses. Some of these PBH are light enough that they will evaporate before structure formation, leaving behind a large curvature fluctuation on small scales. This broad mass distribution of PBH as Dark Matter will be tested in the future by AdvLIGO and LISA interferometers.

The emergence of gravity as a retro-causal post-inflation macro-quantum-coherent holographic vacuum Higgs-Goldstone field

NASA Astrophysics Data System (ADS)

Sarfatti, Jack; Levit, Creon

2009-06-01

We present a model for the origin of gravity, dark energy and dark matter: Dark energy and dark matter are residual pre-inflation false vacuum random zero point energy (w = - 1) of large-scale negative, and short-scale positive pressure, respectively, corresponding to the "zero point" (incoherent) component of a superfluid (supersolid) ground state. Gravity, in contrast, arises from the 2nd order topological defects in the post-inflation virtual "condensate" (coherent) component. We predict, as a consequence, that the LHC will never detect exotic real on-mass-shell particles that can explain dark matter ΩMDM approx 0.23. We also point out that the future holographic dark energy de Sitter horizon is a total absorber (in the sense of retro-causal Wheeler-Feynman action-at-a-distance electrodynamics) because it is an infinite redshift surface for static detectors. Therefore, the advanced Hawking-Unruh thermal radiation from the future de Sitter horizon is a candidate for the negative pressure dark vacuum energy.

Extended nonlinear feedback model for describing episodes of high inflation

NASA Astrophysics Data System (ADS)

Szybisz, Martín A.; Szybisz, Leszek

2017-01-01

An extension of the nonlinear feedback (NLF) formalism to describe regimes of hyper- and high-inflation in economy is proposed in the present work. In the NLF model the consumer price index (CPI) exhibits a finite time singularity of the type 1 /(tc - t) (1 - β) / β, with β > 0, predicting a blow up of the economy at a critical time tc. However, this model fails in determining tc in the case of weak hyperinflation regimes like, e.g., that occurred in Israel. To overcome this trouble, the NLF model is extended by introducing a parameter γ, which multiplies all terms with past growth rate index (GRI). In this novel approach the solution for CPI is also analytic being proportional to the Gaussian hypergeometric function 2F1(1 / β , 1 / β , 1 + 1 / β ; z) , where z is a function of β, γ, and tc. For z → 1 this hypergeometric function diverges leading to a finite time singularity, from which a value of tc can be determined. This singularity is also present in GRI. It is shown that the interplay between parameters β and γ may produce phenomena of multiple equilibria. An analysis of the severe hyperinflation occurred in Hungary proves that the novel model is robust. When this model is used for examining data of Israel a reasonable tc is got. High-inflation regimes in Mexico and Iceland, which exhibit weaker inflations than that of Israel, are also successfully described.

Nonthermal gravitino production in tribrid inflation

NASA Astrophysics Data System (ADS)

Antusch, Stefan; Dutta, Koushik

2015-10-01

We investigate nonthermal gravitino production after tribrid inflation in supergravity, which is a variant of supersymmetric hybrid inflation where three fields are involved in the inflationary model and where the inflaton field resides in the matter sector of the theory. In contrast to conventional supersymmetric hybrid inflation, where nonthermal gravitino production imposes severe constraints on the inflationary model, we find that the "nonthermal gravitino problem" is generically absent in models of tribrid inflation, mainly due to two effects: (i) With the inflaton in tribrid inflation (after inflation) being lighter than the waterfall field, the latter has a second decay channel with a much larger rate than for the decay into gravitinos. This reduces the branching ratio for the decay of the waterfall field into gravitinos. (ii) The inflaton generically decays later than the waterfall field, and it does not produce gravitinos when it decays. This leads to a dilution of the gravitino population from the decays of the waterfall field. The combination of both effects generically leads to a strongly reduced gravitino production in tribrid inflation.

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2012 CFR

2012-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST..., and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced... maintenance of inflatable rescue boats must follow the manufacturers' instructions. Each repair, except an...

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2013 CFR

2013-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST..., and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced... maintenance of inflatable rescue boats must follow the manufacturers' instructions. Each repair, except an...

46 CFR 131.580 - Servicing of inflatable liferafts, inflatable lifejackets, inflatable buoyant apparatus, and...

Code of Federal Regulations, 2014 CFR

2014-10-01

... lifejackets, inflatable buoyant apparatus, and inflated rescue boats. 131.580 Section 131.580 Shipping COAST..., and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant apparatus must be serviced... maintenance of inflatable rescue boats must follow the manufacturers' instructions. Each repair, except an...

Effects of Variable Inflationary Conditions on AN Inventory Model with Inflation-Proportional Demand Rate

NASA Astrophysics Data System (ADS)

Mirzazadeh, Abolfazl

2009-08-01

The inflation rate in the most of the previous researches has been considered constant and well-known over the time horizon, although the future rate of inflation is inherently uncertain and unstable, and is difficult to predict it accurately. Therefore, A time varying inventory model for deteriorating items with allowable shortages is developed in this paper. The inflation rates (internal and external) are time-dependent and demand rate is inflation-proportional. The inventory level is described by differential equations over the time horizon and present value method is used. The numerical example is given to explain the results. Some particular cases, which follow the main problem, will discuss and the results will compare with the main model by using the numerical examples. It has been achieved which shortages increases considerably in comparison with the case of without variable inflationary conditions.

Symmetry breaking patterns for inflation

NASA Astrophysics Data System (ADS)

Klein, Remko; Roest, Diederik; Stefanyszyn, David

2018-06-01

We study inflationary models where the kinetic sector of the theory has a non-linearly realised symmetry which is broken by the inflationary potential. We distinguish between kinetic symmetries which non-linearly realise an internal or space-time group, and which yield a flat or curved scalar manifold. This classification leads to well-known inflationary models such as monomial inflation and α-attractors, as well as a new model based on fixed couplings between a dilaton and many axions which non-linearly realises higher-dimensional conformal symmetries. In this model, inflation can be realised along the dilatonic direction, leading to a tensor-to-scalar ratio r ˜ 0 .01 and a spectral index n s ˜ 0 .975. We refer to the new model as ambient inflation since inflation proceeds along an isometry of an anti-de Sitter ambient space-time, which fully determines the kinetic sector.

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2013 CFR

2013-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD..., inflatable life jackets, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant... other standard specified by the Commandant. (e) Repair and maintenance of inflated rescue boats must be...

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2012 CFR

2012-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD..., inflatable life jackets, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant... other standard specified by the Commandant. (e) Repair and maintenance of inflated rescue boats must be...

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2014 CFR

2014-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD..., inflatable life jackets, and inflated rescue boats. (a) An inflatable liferaft or inflatable buoyant... other standard specified by the Commandant. (e) Repair and maintenance of inflated rescue boats must be...

Impacts of supersymmetric higher derivative terms on inflation models in supergravity

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

Aoki, Shuntaro; Yamada, Yusuke, E-mail: shun-soccer@akane.waseda.jp, E-mail: yuusuke-yamada@asagi.waseda.jp

2015-07-01

We show the effects of supersymmetric higher derivative terms on inflation models in supergravity. The results show that such terms generically modify the effective kinetic coefficient of the inflaton during inflation if the cut off scale of the higher derivative operators is sufficiently small. In such a case, the η-problem in supergravity does not occur, and we find that the effective potential of the inflaton generically becomes a power type potential with a power smaller than two.

Thermalized axion inflation: Natural and monomial inflation with small r

NASA Astrophysics Data System (ADS)

Ferreira, Ricardo Z.; Notari, Alessio

2018-03-01

A safe way to reheat the Universe, in models of natural and quadratic inflation, is through shift symmetric couplings between the inflaton ϕ and the Standard Model (SM), since they do not generate loop corrections to the potential V (ϕ ). We consider such a coupling to SM gauge fields, of the form ϕ F F ˜/f , with sub-Planckian f . In this case, gauge fields can be exponentially produced already during inflation and thermalize via interactions with charged particles, as pointed out in previous work. This can lead to a plasma of temperature T during inflation, and the thermal masses g T of the gauge bosons can equilibrate the system. In addition, inflaton perturbations δ ϕ can also have a thermal spectrum if they have sufficiently large cross sections with the plasma. In this case, inflationary predictions are strongly modified: (1) scalar perturbations are thermal, and so enhanced over the vacuum, leading to a generic way to suppress the tensor-to-scalar ratio r ; (2) the spectral index is ns-1 =η -4 ɛ . After presenting the relevant conditions for thermalization, we show that thermalized natural and monomial models of inflation agree with present observations and have r ≈10-3-10-2, which is within reach of next generation CMB experiments.

Retargeted Least Squares Regression Algorithm.

PubMed

Zhang, Xu-Yao; Wang, Lingfeng; Xiang, Shiming; Liu, Cheng-Lin

2015-09-01

This brief presents a framework of retargeted least squares regression (ReLSR) for multicategory classification. The core idea is to directly learn the regression targets from data other than using the traditional zero-one matrix as regression targets. The learned target matrix can guarantee a large margin constraint for the requirement of correct classification for each data point. Compared with the traditional least squares regression (LSR) and a recently proposed discriminative LSR models, ReLSR is much more accurate in measuring the classification error of the regression model. Furthermore, ReLSR is a single and compact model, hence there is no need to train two-class (binary) machines that are independent of each other. The convex optimization problem of ReLSR is solved elegantly and efficiently with an alternating procedure including regression and retargeting as substeps. The experimental evaluation over a range of databases identifies the validity of our method.

Alchemical inflation: inflaton turns into Higgs

NASA Astrophysics Data System (ADS)

Nakayama, Kazunori; Takahashi, Fuminobu

2012-11-01

We propose a new inflation model in which a gauge singlet inflaton turns into the Higgs condensate after inflation. The inflationary path is characterized by a moduli space of supersymmetric vacua spanned by the inflaton and Higgs field. The inflation energy scale is related to the soft supersymmetry breaking, and the Hubble parameter during inflation is smaller than the gravitino mass. The initial condition for the successful inflation is naturally realized by the pre-inflation in which the Higgs plays a role of the waterfall field.

Coronary artery calcium distributions in older persons in the AGES-Reykjavik study

PubMed Central

Gudmundsson, Elias Freyr; Gudnason, Vilmundur; Sigurdsson, Sigurdur; Launer, Lenore J.; Harris, Tamara B.; Aspelund, Thor

2013-01-01

Coronary Artery Calcium (CAC) is a sign of advanced atherosclerosis and an independent risk factor for cardiac events. Here, we describe CAC-distributions in an unselected aged population and compare modelling methods to characterize CAC-distribution. CAC is difficult to model because it has a skewed and zero inflated distribution with over-dispersion. Data are from the AGES-Reykjavik sample, a large population based study [2002-2006] in Iceland of 5,764 persons aged 66-96 years. Linear regressions using logarithmic- and Box-Cox transformations on CAC+1, quantile regression and a Zero-Inflated Negative Binomial model (ZINB) were applied. Methods were compared visually and with the PRESS-statistic, R2 and number of detected associations with concurrently measured variables. There were pronounced differences in CAC according to sex, age, history of coronary events and presence of plaque in the carotid artery. Associations with conventional coronary artery disease (CAD) risk factors varied between the sexes. The ZINB model provided the best results with respect to the PRESS-statistic, R2, and predicted proportion of zero scores. The ZINB model detected similar numbers of associations as the linear regression on ln(CAC+1) and usually with the same risk factors. PMID:22990371

Topological defects in extended inflation

NASA Technical Reports Server (NTRS)

Copeland, Edmund J.; Kolb, Edward W.; Liddle, Andrew R.

1990-01-01

The production of topological defects, especially cosmic strings, in extended inflation models was considered. In extended inflation, the Universe passes through a first-order phase transition via bubble percolation, which naturally allows defects to form at the end of inflation. The correlation length, which determines the number density of the defects, is related to the mean size of bubbles when they collide. This mechanism allows a natural combination of inflation and large scale structure via cosmic strings.

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2014 CFR

2014-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... liferafts, inflatable buoyant apparatus, inflatable life jackets, and inflated rescue boats. (a) An... inflated rescue boats must be in accordance with the manufacturer's instructions. All repairs must be made...

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2013 CFR

2013-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... liferafts, inflatable buoyant apparatus, inflatable life jackets, and inflated rescue boats. (a) An... inflated rescue boats must be in accordance with the manufacturer's instructions. All repairs must be made...

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2012 CFR

2012-10-01

... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... liferafts, inflatable buoyant apparatus, inflatable life jackets, and inflated rescue boats. (a) An... inflated rescue boats must be in accordance with the manufacturer's instructions. All repairs must be made...

Macro-level pedestrian and bicycle crash analysis: Incorporating spatial spillover effects in dual state count models.

PubMed

Cai, Qing; Lee, Jaeyoung; Eluru, Naveen; Abdel-Aty, Mohamed

2016-08-01

This study attempts to explore the viability of dual-state models (i.e., zero-inflated and hurdle models) for traffic analysis zones (TAZs) based pedestrian and bicycle crash frequency analysis. Additionally, spatial spillover effects are explored in the models by employing exogenous variables from neighboring zones. The dual-state models such as zero-inflated negative binomial and hurdle negative binomial models (with and without spatial effects) are compared with the conventional single-state model (i.e., negative binomial). The model comparison for pedestrian and bicycle crashes revealed that the models that considered observed spatial effects perform better than the models that did not consider the observed spatial effects. Across the models with spatial spillover effects, the dual-state models especially zero-inflated negative binomial model offered better performance compared to single-state models. Moreover, the model results clearly highlighted the importance of various traffic, roadway, and sociodemographic characteristics of the TAZ as well as neighboring TAZs on pedestrian and bicycle crash frequency. Copyright © 2016 Elsevier Ltd. All rights reserved.

An economic order quantity model with shortage and inflation

NASA Astrophysics Data System (ADS)

Wulan, Elis Ratna; Nurjaman, Wildan

2015-09-01

The effect of inflation has become a persistent characteristic and more significant problem of many developing economies especially in the third world countries. While making effort to achieve optimal quantity of product to be produced or purchased using the simplest and on the shelf classical EOQ model, the non-inclusion of conflicting economic realities as shortage and inflation has rendered its result quite uneconomical and hence the purpose for this study. Mathematical expression was developed for each of the cost components the sum of which become the total inventory model over the period (0,L) ((TIC(0,L)). L is planning horizon and TIC(0,L) is total inventory cost over a period of (0,L). Significant savings with increase in quantity was achieved based on deference in the varying price regime. With the assumptions considered and subject to the availability of reliable inventory cost element, the developed model is found to produce a feasible, and economic inventory stock-level with the numerical example of a material supply of a manufacturing company.

Primordial perturbations in multi-scalar inflation

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

Abedi, Habib; Abbassi, Amir M., E-mail: h.abedi@ut.ac.ir, E-mail: amabasi@khayam.ut.ac.ir

2017-07-01

Multiple field models of inflation exhibit new features than single field models. In this work, we study the hierarchy of parameters based on Hubble expansion rate in curved field space and derive the system of flow equations that describe their evolutions. Then we focus on obtaining derivatives of number of e-folds with respect to scalar fields during inflation and at hypersurface of the end of inflation.

Seven lessons from manyfield inflation in random potentials

NASA Astrophysics Data System (ADS)

Dias, Mafalda; Frazer, Jonathan; Marsh, M. C. David

2018-01-01

We study inflation in models with many interacting fields subject to randomly generated scalar potentials. We use methods from non-equilibrium random matrix theory to construct the potentials and an adaption of the `transport method' to evolve the two-point correlators during inflation. This construction allows, for the first time, for an explicit study of models with up to 100 interacting fields supporting a period of `approximately saddle-point' inflation. We determine the statistical predictions for observables by generating over 30,000 models with 2–100 fields supporting at least 60 efolds of inflation. These studies lead us to seven lessons: i) Manyfield inflation is not single-field inflation, ii) The larger the number of fields, the simpler and sharper the predictions, iii) Planck compatibility is not rare, but future experiments may rule out this class of models, iv) The smoother the potentials, the sharper the predictions, v) Hyperparameters can transition from stiff to sloppy, vi) Despite tachyons, isocurvature can decay, vii) Eigenvalue repulsion drives the predictions. We conclude that many of the `generic predictions' of single-field inflation can be emergent features of complex inflation models.

Fibre inflation and α-attractors

NASA Astrophysics Data System (ADS)

Kallosh, Renata; Linde, Andrei; Roest, Diederik; Westphal, Alexander; Yamada, Yusuke

2018-02-01

Fibre inflation is a specific string theory construction based on the Large Volume Scenario that produces an inflationary plateau. We outline its relation to α-attractor models for inflation, with the cosmological sector originating from certain string theory corrections leading to α = 2 and α = 1/2. Above a certain field range, the steepening effect of higher-order corrections leads first to the breakdown of single-field slow-roll and after that to the onset of 2-field dynamics: the overall volume of the extra dimensions starts to participate in the effective dynamics. Finally, we propose effective supergravity models of fibre inflation based on an \\overline{D3} uplift term with a nilpotent superfield. Specific moduli dependent \\overline{D3} induced geometries lead to cosmological fibre models but have in addition a de Sitter minimum exit. These supergravity models motivated by fibre inflation are relatively simple, stabilize the axions and disentangle the Hubble parameter from supersymmetry breaking.

No-scale ripple inflation revisited

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

Li, Tianjun; Li, Zhijin; Nanopoulos, Dimitri V., E-mail: tli@itp.ac.cn, E-mail: lizhijin@physics.tamu.edu, E-mail: dimitri@physics.tamu.edu

We revisit the no-scale ripple inflation model, where no-scale supergravity is modified by an additional term for the inflaton field in the Kähler potential. This term not only breaks one SU(N,1) symmetry explicitly, but also plays an important role for inflation. We generalize the superpotential in the no-scale ripple inflation model slightly. There exists a discrete Z{sub 2} symmetry/parity in the scalar potential in general, which can be preserved or violated by the non-canonical nomalized inflaton kinetic term. Thus, there are three inflation paths: one parity invariant path, and the left and right paths for parity violating scenario. We showmore » that the inflations along the parity invariant path and right path are consistent with the Planck results. However, the gavitino mass for the parity invariant path is so large that the inflation results will be invalid if we consider the inflaton supersymmetry breaking soft mass term. Thus, only the inflation along the right path gives the correct and consistent results. Notably, the tensor-to-scalar ratio in such case can be large, with a value around 0.05, which may be probed by the future Planck experiment.« less

Model selection with multiple regression on distance matrices leads to incorrect inferences.

PubMed

Franckowiak, Ryan P; Panasci, Michael; Jarvis, Karl J; Acuña-Rodriguez, Ian S; Landguth, Erin L; Fortin, Marie-Josée; Wagner, Helene H

2017-01-01

In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM) to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC), its small-sample correction (AICc), and the Bayesian information criterion (BIC) to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Revisiting non-Gaussianity from non-attractor inflation models

NASA Astrophysics Data System (ADS)

Cai, Yi-Fu; Chen, Xingang; Namjoo, Mohammad Hossein; Sasaki, Misao; Wang, Dong-Gang; Wang, Ziwei

2018-05-01

Non-attractor inflation is known as the only single field inflationary scenario that can violate non-Gaussianity consistency relation with the Bunch-Davies vacuum state and generate large local non-Gaussianity. However, it is also known that the non-attractor inflation by itself is incomplete and should be followed by a phase of slow-roll attractor. Moreover, there is a transition process between these two phases. In the past literature, this transition was approximated as instant and the evolution of non-Gaussianity in this phase was not fully studied. In this paper, we follow the detailed evolution of the non-Gaussianity through the transition phase into the slow-roll attractor phase, considering different types of transition. We find that the transition process has important effect on the size of the local non-Gaussianity. We first compute the net contribution of the non-Gaussianities at the end of inflation in canonical non-attractor models. If the curvature perturbations keep evolving during the transition—such as in the case of smooth transition or some sharp transition scenarios—the Script O(1) local non-Gaussianity generated in the non-attractor phase can be completely erased by the subsequent evolution, although the consistency relation remains violated. In extremal cases of sharp transition where the super-horizon modes freeze immediately right after the end of the non-attractor phase, the original non-attractor result can be recovered. We also study models with non-canonical kinetic terms, and find that the transition can typically contribute a suppression factor in the squeezed bispectrum, but the final local non-Gaussianity can still be made parametrically large.

Self-reproduction in k-inflation

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

Helmer, Ferdinand; Winitzki, Sergei

2006-09-15

We study cosmological self-reproduction in models of inflation driven by a scalar field {phi} with a noncanonical kinetic term (k-inflation). We develop a general criterion for the existence of attractors and establish conditions selecting a class of k-inflation models that admit a unique attractor solution. We then consider quantum fluctuations on the attractor background. We show that the correlation length of the fluctuations is of order c{sub s}H{sup -1}, where c{sub s} is the speed of sound. By computing the magnitude of field fluctuations, we determine the coefficients of Fokker-Planck equations describing the probability distribution of the spatially averaged fieldmore » {phi}. The field fluctuations are generally large in the inflationary attractor regime; hence, eternal self-reproduction is a generic feature of k-inflation. This is established more formally by demonstrating the existence of stationary solutions of the relevant Fokker-Planck equations. We also show that there exists a (model-dependent) range {phi}{sub R}<{phi}<{phi}{sub max} within which large fluctuations are likely to drive the field towards the upper boundary {phi}={phi}{sub max}, where the semiclassical consideration breaks down. An exit from inflation into reheating without reaching {phi}{sub max} will occur almost surely (with probability 1) only if the initial value of {phi} is below {phi}{sub R}. In this way, strong self-reproduction effects constrain models of k-inflation.« less

Inflation of Unreefed and Reefed Extraction Parachutes

NASA Technical Reports Server (NTRS)

Ray, Eric S.; Varela, Jose G.

2015-01-01

Data from the Orion and several other test programs have been used to reconstruct inflation parameters for 28 ft Do extraction parachutes as well as the parent aircraft pitch response during extraction. The inflation force generated by extraction parachutes is recorded directly during tow tests but is usually inferred from the payload accelerometer during Low Velocity Airdrop Delivery (LVAD) flight test extractions. Inflation parameters are dependent on the type of parent aircraft, number of canopies, and standard vs. high altitude extraction conditions. For standard altitudes, single canopy inflations are modeled as infinite mass, but the non-symmetric inflations in a cluster are modeled as finite mass. High altitude extractions have necessitated reefing the extraction parachutes, which are best modeled as infinite mass for those conditions. Distributions of aircraft pitch profiles and inflation parameters have been generated for use in Monte Carlo simulations of payload extractions.

Primordial anisotropies in gauged hybrid inflation

NASA Astrophysics Data System (ADS)

Akbar Abolhasani, Ali; Emami, Razieh; Firouzjahi, Hassan

2014-05-01

We study primordial anisotropies generated in the model of gauged hybrid inflation in which the complex waterfall field is charged under a U(1)gauge field. Primordial anisotropies are generated either actively during inflation or from inhomogeneities modulating the surface of end of inflation during waterfall transition. We present a consistent δN mechanism to calculate the anisotropic power spectrum and bispectrum. We show that the primordial anisotropies generated at the surface of end of inflation do not depend on the number of e-folds and therefore do not produce dangerously large anisotropies associated with the IR modes. Furthermore, one can find the parameter space that the anisotropies generated from the surface of end of inflation cancel the anisotropies generated during inflation, therefore relaxing the constrains on model parameters imposed from IR anisotropies. We also show that the gauge field fluctuations induce a red-tilted power spectrum so the averaged power spectrum from the gauge field can change the total power spectrum from blue to red. Therefore, hybrid inflation, once gauged under a U(1) field, can be consistent with the cosmological observations.

Accidental Kähler moduli inflation

NASA Astrophysics Data System (ADS)

Maharana, Anshuman; Rummel, Markus; Sumitomo, Yoske

2015-09-01

We study a model of accidental inflation in type IIB string theory where inflation occurs near the inflection point of a small Kähler modulus. A racetrack structure helps to alleviate the known concern that string-loop corrections may spoil Kähler Moduli Inflation unless having a significant suppression via the string coupling or a special brane setup. Also, the hierarchy of gauge group ranks required for the separation between moduli stabilization and inflationary dynamics is relaxed. The relaxation becomes more significant when we use the recently proposed D-term generated racetrack model.

Evaluating differential effects using regression interactions and regression mixture models

PubMed Central

Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

2015-01-01

Research increasingly emphasizes understanding differential effects. This paper focuses on understanding regression mixture models, a relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The paper aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design. PMID:26556903

Cosmic microwave background probes models of inflation

NASA Technical Reports Server (NTRS)

Davis, Richard L.; Hodges, Hardy M.; Smoot, George F.; Steinhardt, Paul J.; Turner, Michael S.

1992-01-01

Inflation creates both scalar (density) and tensor (gravity wave) metric perturbations. We find that the tensor-mode contribution to the cosmic microwave background anisotropy on large-angular scales can only exceed that of the scalar mode in models where the spectrum of perturbations deviates significantly from scale invariance. If the tensor mode dominates at large-angular scales, then the value of DeltaT/T predicted on 1 deg is less than if the scalar mode dominates, and, for cold-dark-matter models, bias factors greater than 1 can be made consistent with Cosmic Background Explorer (COBE) DMR results.

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2011 CFR

2011-10-01

... inflatable liferaft or inflatable buoyant apparatus must be serviced at a facility specifically approved by... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... Operational Readiness, Maintenance, and Inspection of Lifesaving Equipment § 185.730 Servicing of inflatable...

46 CFR 185.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2010 CFR

2010-10-01

... inflatable liferaft or inflatable buoyant apparatus must be serviced at a facility specifically approved by... apparatus, inflatable life jackets, and inflated rescue boats. 185.730 Section 185.730 Shipping COAST GUARD... Operational Readiness, Maintenance, and Inspection of Lifesaving Equipment § 185.730 Servicing of inflatable...

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

Revisiting Gaussian Process Regression Modeling for Localization in Wireless Sensor Networks

PubMed Central

Richter, Philipp; Toledano-Ayala, Manuel

2015-01-01

Signal strength-based positioning in wireless sensor networks is a key technology for seamless, ubiquitous localization, especially in areas where Global Navigation Satellite System (GNSS) signals propagate poorly. To enable wireless local area network (WLAN) location fingerprinting in larger areas while maintaining accuracy, methods to reduce the effort of radio map creation must be consolidated and automatized. Gaussian process regression has been applied to overcome this issue, also with auspicious results, but the fit of the model was never thoroughly assessed. Instead, most studies trained a readily available model, relying on the zero mean and squared exponential covariance function, without further scrutinization. This paper studies the Gaussian process regression model selection for WLAN fingerprinting in indoor and outdoor environments. We train several models for indoor/outdoor- and combined areas; we evaluate them quantitatively and compare them by means of adequate model measures, hence assessing the fit of these models directly. To illuminate the quality of the model fit, the residuals of the proposed model are investigated, as well. Comparative experiments on the positioning performance verify and conclude the model selection. In this way, we show that the standard model is not the most appropriate, discuss alternatives and present our best candidate. PMID:26370996

Tribrid Inflation in Supergravity

NASA Astrophysics Data System (ADS)

Antusch, Stefan; Dutta, Koushik; Kostka, Philipp M.

We propose a novel class of F-term hybrid inflation models in supergravity (SUGRA) where the η-problem is resolved using either a Heisenberg symmetry or a shift symmetry of the Kähler potential. In addition to the inflaton and the waterfall field, this class (referred to as tribrid inflation) contains a third "driving" field which contributes the large vacuum energy during inflation by its F-term. In contrast to the "standard" hybrid scenario, it has several attractive features due to the property of vanishing inflationary superpotential (Winf = 0) during inflation. Quantum corrections induced by symmetry breaking terms in the superpotential generate a slope of the potential and lead to a spectral tilt consistent with recent WMAP observations.

Numerical modelling of Mars supersonic disk-gap-band parachute inflation

NASA Astrophysics Data System (ADS)

Gao, Xinglong; Zhang, Qingbin; Tang, Qiangang

2016-06-01

The transient dynamic behaviour of supersonic disk-gap-band parachutes in a Mars entry environment involving fluid structure interactions is studied. Based on the multi-material Arbitrary Lagrange-Euler method, the coupling dynamic model between a viscous compressible fluid and a flexible large deformation structure of the parachute is solved. The inflation performance of a parachute with a fixed forebody under different flow conditions is analysed. The decelerating parameters of the parachute, including drag area, opening loads, and coefficients, are obtained from the supersonic wind tunnel test data from NASA. Meanwhile, the evolution of the three-dimensional shape of the disk-gap-band parachute during supersonic inflation is presented, and the structural dynamic behaviour of the parachute is predicted. Then, the influence of the presence of the capsule on the flow field of the parachute is investigated, and the wake of unsteady fluid and the distribution of shock wave around the supersonic parachute are presented. Finally, the structural dynamic response of the canopy fabric under high-pressure conditions is comparatively analysed. The results show that the disk-gap-band parachute is well inflated without serious collapse. As the Mach numbers increase from 2.0 to 2.5, the drag coefficients gradually decrease, along with a small decrease in inflation time, which corresponds with test results, and proves the validity of the method proposed in this paper.

Stochastic effects in hybrid inflation

NASA Astrophysics Data System (ADS)

Martin, Jérôme; Vennin, Vincent

2012-02-01

Hybrid inflation is a two-field model where inflation ends due to an instability. In the neighborhood of the instability point, the potential is very flat and the quantum fluctuations dominate over the classical motion of the inflaton and waterfall fields. In this article, we study this regime in the framework of stochastic inflation. We numerically solve the two coupled Langevin equations controlling the evolution of the fields and compute the probability distributions of the total number of e-folds and of the inflation exit point. Then, we discuss the physical consequences of our results, in particular, the question of how the quantum diffusion can affect the observable predictions of hybrid inflation.

Beyond Inflation:. A Cyclic Universe Scenario

NASA Astrophysics Data System (ADS)

Turok, Neil; Steinhardt, Paul J.

2005-08-01

Inflation has been the leading early universe scenario for two decades, and has become an accepted element of the successful 'cosmic concordance' model. However, there are many puzzling features of the resulting theory. It requires both high energy and low energy inflation, with energy densities differing by a hundred orders of magnitude. The questions of why the universe started out undergoing high energy inflation, and why it will end up in low energy inflation, are unanswered. Rather than resort to anthropic arguments, we have developed an alternative cosmology, the cyclic universe [1], in which the universe exists in a very long-lived attractor state determined by the laws of physics. The model shares inflation's phenomenological successes without requiring an epoch of high energy inflation. Instead, the universe is made homogeneous and flat, and scale-invariant adiabatic perturbations are generated during an epoch of low energy acceleration like that seen today, but preceding the last big bang. Unlike inflation, the model requires low energy acceleration in order for a periodic attractor state to exist. The key challenge facing the scenario is that of passing through the cosmic singularity at t = 0. Substantial progress has been made at the level of linearised gravity, which is reviewed here. The challenge of extending this to nonlinear gravity and string theory remains.

Beyond Inflation: A Cyclic Universe Scenario

NASA Astrophysics Data System (ADS)

Turok, Neil; Steinhardt, Paul J.

2005-01-01

Inflation has been the leading early universe scenario for two decades, and has become an accepted element of the successful `cosmic concordance' model. However, there are many puzzling features of the resulting theory. It requires both high energy and low energy inflation, with energy densities differing by a hundred orders of magnitude. The questions of why the universe started out undergoing high energy inflation, and why it will end up in low energy inflation, are unanswered. Rather than resort to anthropic arguments, we have developed an alternative cosmology, the cyclic universe, in which the universe exists in a very long-lived attractor state determined by the laws of physics. The model shares inflation's phenomenological successes without requiring an epoch of high energy inflation. Instead, the universe is made homogeneous and flat, and scale-invariant adiabatic perturbations are generated during an epoch of low energy acceleration like that seen today, but preceding the last big bang. Unlike inflation, the model requires low energy acceleration in order for a periodic attractor state to exist. The key challenge facing the scenario is that of passing through the cosmic singularity at t = 0. Substantial progress has been made at the level of linearised gravity, which is reviewed here. The challenge of extending this to nonlinear gravity and string theory remains.

Open inflation in the landscape

NASA Astrophysics Data System (ADS)

Yamauchi, Daisuke; Linde, Andrei; Naruko, Atsushi; Sasaki, Misao; Tanaka, Takahiro

2011-08-01

The open inflation scenario is attracting a renewed interest in the context of the string landscape. Since there are a large number of metastable de Sitter vacua in the string landscape, tunneling transitions to lower metastable vacua through the bubble nucleation occur quite naturally, which leads to a natural realization of open inflation. Although the deviation of Ω0 from unity is small by the observational bound, we argue that the effect of this small deviation on the large-angle CMB anisotropies can be significant for tensor-type perturbation in the open inflation scenario. We consider the situation in which there is a large hierarchy between the energy scale of the quantum tunneling and that of the slow-roll inflation in the nucleated bubble. If the potential just after tunneling is steep enough, a rapid-roll phase appears before the slow-roll inflation. In this case the power spectrum is basically determined by the Hubble rate during the slow-roll inflation. On the other hand, if such a rapid-roll phase is absent, the power spectrum keeps the memory of the high energy density there in the large angular components. Furthermore, the amplitude of large angular components can be enhanced due to the effects of the wall fluctuation mode if the bubble wall tension is small. Therefore, although even the dominant quadrupole component is suppressed by the factor (1-Ω0)2, one can construct some models in which the deviation of Ω0 from unity is large enough to produce measurable effects. We also consider a more general class of models, where the false vacuum decay may occur due to Hawking-Moss tunneling, as well as the models involving more than one scalar field. We discuss scalar perturbations in these models and point out that a large set of such models is already ruled out by observational data, unless there was a very long stage of slow-roll inflation after the tunneling. These results show that observational data allow us to test various assumptions concerning

Natural inflation and quantum gravity.

PubMed

de la Fuente, Anton; Saraswat, Prashant; Sundrum, Raman

2015-04-17

Cosmic inflation provides an attractive framework for understanding the early Universe and the cosmic microwave background. It can readily involve energies close to the scale at which quantum gravity effects become important. General considerations of black hole quantum mechanics suggest nontrivial constraints on any effective field theory model of inflation that emerges as a low-energy limit of quantum gravity, in particular, the constraint of the weak gravity conjecture. We show that higher-dimensional gauge and gravitational dynamics can elegantly satisfy these constraints and lead to a viable, theoretically controlled and predictive class of natural inflation models.

Type I error rates of rare single nucleotide variants are inflated in tests of association with non-normally distributed traits using simple linear regression methods.

PubMed

Schwantes-An, Tae-Hwi; Sung, Heejong; Sabourin, Jeremy A; Justice, Cristina M; Sorant, Alexa J M; Wilson, Alexander F

2016-01-01

In this study, the effects of (a) the minor allele frequency of the single nucleotide variant (SNV), (b) the degree of departure from normality of the trait, and (c) the position of the SNVs on type I error rates were investigated in the Genetic Analysis Workshop (GAW) 19 whole exome sequence data. To test the distribution of the type I error rate, 5 simulated traits were considered: standard normal and gamma distributed traits; 2 transformed versions of the gamma trait (log 10 and rank-based inverse normal transformations); and trait Q1 provided by GAW 19. Each trait was tested with 313,340 SNVs. Tests of association were performed with simple linear regression and average type I error rates were determined for minor allele frequency classes. Rare SNVs (minor allele frequency < 0.05) showed inflated type I error rates for non-normally distributed traits that increased as the minor allele frequency decreased. The inflation of average type I error rates increased as the significance threshold decreased. Normally distributed traits did not show inflated type I error rates with respect to the minor allele frequency for rare SNVs. There was no consistent effect of transformation on the uniformity of the distribution of the location of SNVs with a type I error.

Degravitation, inflation and the cosmological constant as an afterglow

NASA Astrophysics Data System (ADS)

Patil, Subodh P.

2009-01-01

In this report, we adopt the phenomenological approach of taking the degravitation paradigm seriously as a consistent modification of gravity in the IR, and investigate its consequences for various cosmological situations. We motivate degravitation — where Netwon's constant is promoted to a scale dependent filter function — as arising from either a small (resonant) mass for the graviton, or as an effect in semi-classical gravity. After addressing how the Bianchi identities are to be satisfied in such a set up, we turn our attention towards the cosmological consequences of degravitation. By considering the example filter function corresponding to a resonantly massive graviton (with a filter scale larger than the present horizon scale), we show that slow roll inflation, hybrid inflation and old inflation remain quantitatively unchanged. We also find that the degravitation mechanism inherits a memory of past energy densities in the present epoch in such a way that is likely significant for present cosmological evolution. For example, if the universe underwent inflation in the past due to it having tunneled out of some false vacuum, we find that degravitation implies a remnant `afterglow' cosmological constant, whose scale immediately afterwards is parametrically suppressed by the filter scale (L) in Planck units Λ ~ l2pl/L2. We discuss circumstances through which this scenario reasonably yields the presently observed value for Λ ~ O(10-120). We also find that in a universe still currently trapped in some false vacuum state, resonance graviton models of degravitation only degravitate initially Planck or GUT scale energy densities down to the presently observed value over timescales comparable to the filter scale. We argue that different functional forms for the filter function will yield similar conclusions. In this way, we argue that although the degravitation models we study have the potential to explain why the cosmological constant is not large in addition to

Observational constraints on successful model of quintessential Inflation

NASA Astrophysics Data System (ADS)

Geng, Chao-Qiang; Lee, Chung-Chi; Sami, M.; Saridakis, Emmanuel N.; Starobinsky, Alexei A.

2017-06-01

We study quintessential inflation using a generalized exponential potential V(phi)propto \\exp(-λ phin/MPln), n>1, the model admits slow-roll inflation at early times and leads to close-to-scaling behaviour in the post inflationary era with an exit to dark energy at late times. We present detailed investigations of the inflationary stage in the light of the Planck 2015 results, study post-inflationary dynamics and analytically confirm the existence of an approximately scaling solution. Additionally, assuming that standard massive neutrinos are non-minimally coupled, makes the field phi dominant once again at late times giving rise to present accelerated expansion of the Universe. We derive observational constraints on the field and time-dependent neutrino masses. In particular, for n=6 (8), the parameter λ is constrained to be, log λ > -7.29 (-11.7) the model produces the spectral index of the power spectrum of primordial scalar (matter density) perturbations as ns = 0.959 ± 0.001 (0.961 ± 0.001) and tiny tensor-to-scalar ratio, r<1.72 × 10-2 (2.32 × 10-2) respectively. Consequently, the upper bound on possible values of the sum of neutrino masses Σ mν lesssim 2.5 eV significantly enhances compared to that in the standard ΛCDM model.

46 CFR 131.865 - Inflatable liferafts and inflatable buoyant apparatus.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Inflatable liferafts and inflatable buoyant apparatus... SUPPLY VESSELS OPERATIONS Markings for Fire Equipment and Emergency Equipment § 131.865 Inflatable liferafts and inflatable buoyant apparatus. The number of the inflatable liferaft or inflatable buoyant...

46 CFR 131.865 - Inflatable liferafts and inflatable buoyant apparatus.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Inflatable liferafts and inflatable buoyant apparatus... SUPPLY VESSELS OPERATIONS Markings for Fire Equipment and Emergency Equipment § 131.865 Inflatable liferafts and inflatable buoyant apparatus. The number of the inflatable liferaft or inflatable buoyant...

Chameleon field dynamics during inflation

NASA Astrophysics Data System (ADS)

Saba, Nasim; Farhoudi, Mehrdad

By studying the chameleon model during inflation, we investigate whether it can be a successful inflationary model, wherein we employ the common typical potential usually used in the literature. Thus, in the context of the slow-roll approximations, we obtain the e-folding number for the model to verify the ability of resolving the problems of standard big bang cosmology. Meanwhile, we apply the constraints on the form of the chosen potential and also on the equation of state parameter coupled to the scalar field. However, the results of the present analysis show that there is not much chance of having the chameleonic inflation. Hence, we suggest that if through some mechanism the chameleon model can be reduced to the standard inflationary model, then it may cover the whole era of the universe from the inflation up to the late time.

Functional Linear Model with Zero-value Coefficient Function at Sub-regions.

PubMed

Zhou, Jianhui; Wang, Nae-Yuh; Wang, Naisyin

2013-01-01

We propose a shrinkage method to estimate the coefficient function in a functional linear regression model when the value of the coefficient function is zero within certain sub-regions. Besides identifying the null region in which the coefficient function is zero, we also aim to perform estimation and inferences for the nonparametrically estimated coefficient function without over-shrinking the values. Our proposal consists of two stages. In stage one, the Dantzig selector is employed to provide initial location of the null region. In stage two, we propose a group SCAD approach to refine the estimated location of the null region and to provide the estimation and inference procedures for the coefficient function. Our considerations have certain advantages in this functional setup. One goal is to reduce the number of parameters employed in the model. With a one-stage procedure, it is needed to use a large number of knots in order to precisely identify the zero-coefficient region; however, the variation and estimation difficulties increase with the number of parameters. Owing to the additional refinement stage, we avoid this necessity and our estimator achieves superior numerical performance in practice. We show that our estimator enjoys the Oracle property; it identifies the null region with probability tending to 1, and it achieves the same asymptotic normality for the estimated coefficient function on the non-null region as the functional linear model estimator when the non-null region is known. Numerically, our refined estimator overcomes the shortcomings of the initial Dantzig estimator which tends to under-estimate the absolute scale of non-zero coefficients. The performance of the proposed method is illustrated in simulation studies. We apply the method in an analysis of data collected by the Johns Hopkins Precursors Study, where the primary interests are in estimating the strength of association between body mass index in midlife and the quality of life in

Chaotic inflation from nonlinear sigma models in supergravity

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

Hellerman, Simeon; Kehayias, John; Yanagida, Tsutomu T.

2015-02-11

We present a common solution to the puzzles of the light Higgs or quark masses and the need for a shift symmetry and large field values in high scale chaotic inflation. One way to protect, for example, the Higgs from a large supersymmetric mass term is if it is the Nambu–Goldstone boson (NGB) of a nonlinear sigma model. However, it is well known that nonlinear sigma models (NLSMs) with nontrivial Kähler transformations are problematic to couple to supergravity. An additional field is necessary to make theKähler potential of the NLSM invariant in supergravity. This field must have a shift symmetrymore » — making it a candidate for the inflaton (or axion). We give an explicit example of such a model for the coset space SU(3)/SU(2) × U(1), with the Higgs as the NGB, including breaking the inflaton’s shift symmetry and producing a chaotic inflation potential. This construction can also be applied to other models, such as one based on E₇/SO(10) × U(1) × U(1) which incorporates the first two generations of (light) quarks as the Nambu–Goldstone multiplets, and has an axion in addition to the inflaton. Along the way we clarify and connect previous work on understanding NLSMs in supergravity and the origin of the extra field (which is the inflaton here), including a connection to Witten–Bagger quantization. This framework has wide applications to model building; a light particle from a NLSM requires, in supergravity, exactly the structure for chaotic inflaton or an axion« less

Inflation and the Capital Budgeting Process.

DTIC Science & Technology

1985-04-01

model . [10:22] Friend, Landskroner and Losq assert that the traditional capital asset pricing model *( CAPM ...value (NPV) capital budgeting model is used extensively in this report and the Consumer Price Index - Urban (CPI-U) and the Wholesale Price Index (WPI...general price level adjustments into the capital budgeting model . The consideration of inflation risk is also warranted. The effects of inflation

Nonlinear Pressurization and Modal Analysis Procedure for Dynamic Modeling of Inflatable Structures

NASA Technical Reports Server (NTRS)

Smalley, Kurt B.; Tinker, Michael L.; Saxon, Jeff (Technical Monitor)

2002-01-01

An introduction and set of guidelines for finite element dynamic modeling of nonrigidized inflatable structures is provided. A two-step approach is presented, involving 1) nonlinear static pressurization of the structure and updating of the stiffness matrix and 2) hear normal modes analysis using the updated stiffness. Advantages of this approach are that it provides physical realism in modeling of pressure stiffening, and it maintains the analytical convenience of a standard bear eigensolution once the stiffness has been modified. Demonstration of the approach is accomplished through the creation and test verification of an inflated cylinder model using a large commercial finite element code. Good frequency and mode shape comparisons are obtained with test data and previous modeling efforts, verifying the accuracy of the technique. Problems encountered in the application of the approach, as well as their solutions, are discussed in detail.

The observational constraint on constant-roll inflation

NASA Astrophysics Data System (ADS)

Gao, Qing

2018-07-01

We discuss the constant-roll inflation with constant ɛ2 and constant \\bar η . By using the method of Bessel function approximation, the analytical expressions for the scalar and tensor power spectra, the scalar and tensor spectral tilts, and the tensor to scalar ratio are derived up to the first order of ɛ1. The model with constant ɛ2 is ruled out by the observations at the 3σ confidence level, and the model with constant \\bar η is consistent with the observations at the 1σ confidence level. The potential for the model with constant \\bar η is also obtained from the Hamilton-Jacobi equation. Although the observations constrain the constant-roll inflation to be the slow-roll inflation, the n s- r results from the constant-roll inflation are not the same as those from the slow-roll inflation even when \\bar η 0.01.

Inflatable Dark Matter.

PubMed

Davoudiasl, Hooman; Hooper, Dan; McDermott, Samuel D

2016-01-22

We describe a general scenario, dubbed "inflatable dark matter," in which the density of dark matter particles can be reduced through a short period of late-time inflation in the early Universe. The overproduction of dark matter that is predicted within many, otherwise, well-motivated models of new physics can be elegantly remedied within this context. Thermal relics that would, otherwise, be disfavored can easily be accommodated within this class of scenarios, including dark matter candidates that are very heavy or very light. Furthermore, the nonthermal abundance of grand unified theory or Planck scale axions can be brought to acceptable levels without invoking anthropic tuning of initial conditions. A period of late-time inflation could have occurred over a wide range of scales from ∼MeV to the weak scale or above, and could have been triggered by physics within a hidden sector, with small but not necessarily negligible couplings to the standard model.

Higgs Inflation in f(Φ, r) Theory

NASA Astrophysics Data System (ADS)

Chakravarty, Girish Kumar; Mohanty, Subhendra; Singh, Naveen K.

2014-02-01

We generalize the scalar-curvature coupling model ξΦ2R of Higgs inflation to ξΦaRb to study inflation. We compute the amplitude and spectral index of curvature perturbations generated during inflation and fix the parameters of the model by comparing these with the Planck + WP data. We find that if the scalar self-coupling λ is in the range 10-5-0.1, parameter a in the range 2.3-3.6 and b in the range 0.77-0.22 at the Planck scale, one can have a viable inflation model even for ξ ≃ 1. The tensor to scalar ratio r in this model is small and our model with scalar-curvature couplings is not ruled out by observational limits on r unlike the pure (λ )/(4) Φ 4 theory. By requiring the curvature coupling parameter to be of order unity, we have evaded the problem of unitarity violation in scalar-graviton scatterings which plague the ξΦ2R Higgs inflation models. We conclude that the Higgs field may still be a good candidate for being the inflaton in the early universe if one considers higher-dimensional curvature coupling.

The relationship between inflation and inflation uncertainty. Empirical evidence for the newest EU countries.

PubMed

Viorica, Daniela; Jemna, Danut; Pintilescu, Carmen; Asandului, Mircea

2014-01-01

The objective of this paper is to verify the hypotheses presented in the literature on the causal relationship between inflation and its uncertainty, for the newest EU countries. To ensure the robustness of the results, in the study four models for inflation uncertainty are estimated in parallel: ARCH (1), GARCH (1,1), EGARCH (1,1,1) and PARCH (1,1,1). The Granger method is used to test the causality between two variables. The working hypothesis is that groups of countries with a similar political and economic background in 1990 and are likely to be characterized by the same causal relationship between inflation and inflation uncertainty. Empirical results partially confirm this hypothesis. C22, E31, E37.

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2011 CFR

2011-10-01

... Inspection of Lifesaving Equipment § 122.730 Servicing of inflatable liferafts, inflatable buoyant apparatus... apparatus must be serviced at a facility specifically approved by the Commandant for the particular brand... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD...

46 CFR 122.730 - Servicing of inflatable liferafts, inflatable buoyant apparatus, inflatable life jackets, and...

Code of Federal Regulations, 2010 CFR

2010-10-01

... Inspection of Lifesaving Equipment § 122.730 Servicing of inflatable liferafts, inflatable buoyant apparatus... apparatus must be serviced at a facility specifically approved by the Commandant for the particular brand... apparatus, inflatable life jackets, and inflated rescue boats. 122.730 Section 122.730 Shipping COAST GUARD...

INFLATE: INFlate Landing Apparatus Technology

NASA Astrophysics Data System (ADS)

Koryanov, V. V. K.; Da-Poian, V. D. P.

2018-02-01

Our project, named INFLATE (INFlatable Landing Apparatus Technology), aims at reducing space landing risks and constraints and so optimizing space missions (reducing cost, mass, and risk and in the same time improving performance).

Computational knee ligament modeling using experimentally determined zero-load lengths.

PubMed

Bloemker, Katherine H; Guess, Trent M; Maletsky, Lorin; Dodd, Kevin

2012-01-01

This study presents a subject-specific method of determining the zero-load lengths of the cruciate and collateral ligaments in computational knee modeling. Three cadaver knees were tested in a dynamic knee simulator. The cadaver knees also underwent manual envelope of motion testing to find their passive range of motion in order to determine the zero-load lengths for each ligament bundle. Computational multibody knee models were created for each knee and model kinematics were compared to experimental kinematics for a simulated walk cycle. One-dimensional non-linear spring damper elements were used to represent cruciate and collateral ligament bundles in the knee models. This study found that knee kinematics were highly sensitive to altering of the zero-load length. The results also suggest optimal methods for defining each of the ligament bundle zero-load lengths, regardless of the subject. These results verify the importance of the zero-load length when modeling the knee joint and verify that manual envelope of motion measurements can be used to determine the passive range of motion of the knee joint. It is also believed that the method described here for determining zero-load length can be used for in vitro or in vivo subject-specific computational models.

Computational Knee Ligament Modeling Using Experimentally Determined Zero-Load Lengths

PubMed Central

Bloemker, Katherine H; Guess, Trent M; Maletsky, Lorin; Dodd, Kevin

2012-01-01

This study presents a subject-specific method of determining the zero-load lengths of the cruciate and collateral ligaments in computational knee modeling. Three cadaver knees were tested in a dynamic knee simulator. The cadaver knees also underwent manual envelope of motion testing to find their passive range of motion in order to determine the zero-load lengths for each ligament bundle. Computational multibody knee models were created for each knee and model kinematics were compared to experimental kinematics for a simulated walk cycle. One-dimensional non-linear spring damper elements were used to represent cruciate and collateral ligament bundles in the knee models. This study found that knee kinematics were highly sensitive to altering of the zero-load length. The results also suggest optimal methods for defining each of the ligament bundle zero-load lengths, regardless of the subject. These results verify the importance of the zero-load length when modeling the knee joint and verify that manual envelope of motion measurements can be used to determine the passive range of motion of the knee joint. It is also believed that the method described here for determining zero-load length can be used for in vitro or in vivo subject-specific computational models. PMID:22523522

Variability of the 2014-present inflation source at Mauna Loa volcano revealed using time-dependent modeling

NASA Astrophysics Data System (ADS)

Johanson, I. A.; Miklius, A.; Okubo, P.; Montgomery-Brown, E. K.

2017-12-01

Mauna Loa volcano is the largest active volcano on earth and in the 20thcentury produced roughly one eruption every seven years. The 33-year quiescence since its last eruption 1984 has been punctuated by three inflation episodes where magma likely entered the shallow plumbing system, but was not erupted. The most recent began in 2014 and is ongoing. Unlike prior inflation episodes, the current one is accompanied by a significant increase in shallow seismicity, a pattern that is similar to earlier pre-eruptive periods. We apply the Kalman filter based Network Inversion Filter (NIF) to the 2014-present inflation episode using data from a 27 station continuous GPS network on Mauna Loa. The model geometry consists of a point volume source and tabular, dike-like body, which have previously been shown to provide a good fit to deformation data from a 2004-2009 inflation episode. The tabular body is discretized into 1km x 1km segments. For each day, the NIF solves for the rates of opening on the tabular body segments (subject to smoothing and positivity constraints), volume change rate in the point source, and slip rate on a deep décollement fault surface, which is constrained to a constant (no transient slip allowed). The Kalman filter in the NIF provides for smoothing both forwards and backwards in time. The model shows that the 2014-present inflation episode occurred as several sub-events, rather than steady inflation. It shows some spatial variability in the location of the inflation sub-events. In the model, opening in the tabular body is initially concentrated below the volcano's summit, in an area roughly outlined by shallow seismicity. In October, 2015 opening in the tabular body shifts to be centered beneath the southwest portion of the summit and seismicity becomes concentrated in this area. By late 2016, the opening rate on the tabular body decreases and is once again under the central part of summit. This modeling approach has allowed us to track these

Primordial blackholes and gravitational waves for an inflection-point model of inflation

NASA Astrophysics Data System (ADS)

Choudhury, Sayantan; Mazumdar, Anupam

2014-06-01

In this article we provide a new closed relationship between cosmic abundance of primordial gravitational waves and primordial blackholes that originated from initial inflationary perturbations for inflection-point models of inflation where inflation occurs below the Planck scale. The current Planck constraint on tensor-to-scalar ratio, running of the spectral tilt, and from the abundance of dark matter content in the universe, we can deduce a strict bound on the current abundance of primordial blackholes to be within a range, 9.99712 ×10-3 <ΩPBHh2 < 9.99736 ×10-3.

Is there scale-dependent bias in single-field inflation?

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

De Putter, Roland; Doré, Olivier; Green, Daniel, E-mail: rdputter@caltech.edu, E-mail: Olivier.P.Dore@jpl.nasa.gov, E-mail: drgreen@cita.utoronto.ca

2015-10-01

Scale-dependent halo bias due to local primordial non-Gaussianity provides a strong test of single-field inflation. While it is universally understood that single-field inflation predicts negligible scale-dependent bias compared to current observational uncertainties, there is still disagreement on the exact level of scale-dependent bias at a level that could strongly impact inferences made from future surveys. In this paper, we clarify this confusion and derive in various ways that there is exactly zero scale-dependent bias in single-field inflation. Much of the current confusion follows from the fact that single-field inflation does predict a mode coupling of matter perturbations at the levelmore » of f{sub NL}{sup local}; ≈ −5/3, which naively would lead to scale-dependent bias. However, we show explicitly that this mode coupling cancels out when perturbations are evaluated at a fixed physical scale rather than fixed coordinate scale. Furthermore, we show how the absence of scale-dependent bias can be derived easily in any gauge. This result can then be incorporated into a complete description of the observed galaxy clustering, including the previously studied general relativistic terms, which are important at the same level as scale-dependent bias of order f{sub NL}{sup local} ∼ 1. This description will allow us to draw unbiased conclusions about inflation from future galaxy clustering data.« less

Baby Skyrme model and fermionic zero modes

NASA Astrophysics Data System (ADS)

Queiruga, J. M.

2016-09-01

In this work we investigate some features of the fermionic sector of the supersymmetric version of the baby Skyrme model. We find that, in the background of Bogomol'nyi-Prasad-Sommerfield compact baby Skyrmions, fermionic zero modes are confined to the defect core. Further, we show that, while three Supersymmetry (SUSY) generators are broken in the defect core, SUSY is completely restored outside. We study also the effect of a D-term deformation of the model. Such a deformation allows for the existence of fermionic zero modes and broken SUSY outside the compact defect.

Perceptual disturbances predicted in zero-g through three-dimensional modeling.

PubMed

Holly, Jan E

2003-01-01

Perceptual disturbances in zero-g and 1-g differ. For example, the vestibular coriolis (or "cross-coupled") effect is weaker in zero-g. In 1-g, blindfolded subjects rotating on-axis experience perceptual disturbances upon head tilt, but the effects diminish in zero-g. Head tilts during centrifugation in zero-g and 1-g are investigated here by means of three-dimensional modeling, using a model that was previously used to explain the zero-g reduction of the on-axis vestibular coriolis effect. The model's foundation comprises the laws of physics, including linear-angular interactions in three dimensions. Addressed is the question: In zero-g, will the vestibular coriolis effect be as weak during centrifugation as during on-axis rotation? Centrifugation in 1-g was simulated first, with the subject supine, head toward center. The most noticeable result concerned direction of head yaw. For clockwise centrifuge rotation, greater perceptual effects arose in simulations during yaw counterclockwise (as viewed from the top of the head) than for yaw clockwise. Centrifugation in zero-g was then simulated with the same "supine" orientation. The result: In zero-g the simulated vestibular coriolis effect was greater during centrifugation than during on-axis rotation. In addition, clockwise-counterclockwise differences did not appear in zero-g, in contrast to the differences that appear in 1-g.

Hilltop supernatural inflation and SUSY unified models

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

Kohri, Kazunori; Lim, C.S.; Lin, Chia-Min

2014-01-01

In this paper, we consider high scale (100TeV) supersymmetry (SUSY) breaking and realize the idea of hilltop supernatural inflation in concrete particle physics models based on flipped-SU(5)and Pati-Salam models in the framework of supersymmetric grand unified theories (SUSY GUTs). The inflaton can be a flat direction including right-handed sneutrino and the waterfall field is a GUT Higgs. The spectral index is n{sub s} = 0.96 which fits very well with recent data by PLANCK satellite. There is no both thermal and non-thermal gravitino problems. Non-thermal leptogenesis can be resulted from the decay of right-handed sneutrino which plays (part of) themore » role of inflaton.« less

Hilltop supernatural inflation and SUSY unified models

NASA Astrophysics Data System (ADS)

Kohri, Kazunori; Lim, C. S.; Lin, Chia-Min; Mimura, Yukihiro

2014-01-01

In this paper, we consider high scale (100TeV) supersymmetry (SUSY) breaking and realize the idea of hilltop supernatural inflation in concrete particle physics models based on flipped-SU(5)and Pati-Salam models in the framework of supersymmetric grand unified theories (SUSY GUTs). The inflaton can be a flat direction including right-handed sneutrino and the waterfall field is a GUT Higgs. The spectral index is ns = 0.96 which fits very well with recent data by PLANCK satellite. There is no both thermal and non-thermal gravitino problems. Non-thermal leptogenesis can be resulted from the decay of right-handed sneutrino which plays (part of) the role of inflaton.

Very low scale Coleman-Weinberg inflation with nonminimal coupling

NASA Astrophysics Data System (ADS)

Kaneta, Kunio; Seto, Osamu; Takahashi, Ryo

2018-03-01

We study viable small-field Coleman-Weinberg (CW) inflation models with the help of nonminimal coupling to gravity. The simplest small-field CW inflation model (with a low-scale potential minimum) is incompatible with the cosmological constraint on the scalar spectral index. However, there are possibilities to make the model realistic. First, we revisit the CW inflation model supplemented with a linear potential term. We next consider the CW inflation model with a logarithmic nonminimal coupling and illustrate that the model can open a new viable parameter space that includes the model with a linear potential term. We also show parameter spaces where the Hubble scale during the inflation can be as small as 10-4 GeV , 1 GeV, 1 04 GeV , and 1 08 GeV for the number of e -folds of 40, 45, 50, and 55, respectively, with other cosmological constraints being satisfied.

Regression modeling of ground-water flow

USGS Publications Warehouse

Cooley, R.L.; Naff, R.L.

1985-01-01

Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

Observational constraints on successful model of quintessential Inflation

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

Geng, Chao-Qiang; Lee, Chung-Chi; Sami, M.

We study quintessential inflation using a generalized exponential potential V (φ)∝ exp(−λ φ {sup n} / M {sub Pl} {sup n} ), n >1, the model admits slow-roll inflation at early times and leads to close-to-scaling behaviour in the post inflationary era with an exit to dark energy at late times. We present detailed investigations of the inflationary stage in the light of the Planck 2015 results, study post-inflationary dynamics and analytically confirm the existence of an approximately scaling solution. Additionally, assuming that standard massive neutrinos are non-minimally coupled, makes the field φ dominant once again at late times givingmore » rise to present accelerated expansion of the Universe. We derive observational constraints on the field and time-dependent neutrino masses. In particular, for n =6 (8), the parameter λ is constrained to be, log λ > −7.29 (−11.7); the model produces the spectral index of the power spectrum of primordial scalar (matter density) perturbations as n {sub s} = 0.959 ± 0.001 (0.961 ± 0.001) and tiny tensor-to-scalar ratio, r <1.72 × 10{sup −2} (2.32 × 10{sup −2}) respectively. Consequently, the upper bound on possible values of the sum of neutrino masses Σ m {sub ν} ∼< 2.5 eV significantly enhances compared to that in the standard ΛCDM model.« less

Tribrid Inflation in Supergravity

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

Antusch, Stefan; Dutta, Koushik; Kostka, Philipp M.

2010-02-10

We propose a novel class of F-term hybrid inflation models in supergravity (SUGRA) where the eta-problem is resolved using either a Heisenberg symmetry or a shift symmetry of the Kaehler potential. In addition to the inflaton and the waterfall field, this class (referred to as tribrid inflation) contains a third 'driving' field which contributes the large vacuum energy during inflation by its F-term. In contrast to the 'standard' hybrid scenario, it has several attractive features due to the property of vanishing inflationary superpotential (W{sub inf} = 0) during inflation. While the symmetries of the Kaehler potential ensure a flat inflatonmore » potential at tree-level, quantum corrections induced by symmetry breaking terms in the superpotential generate a slope of the potential and lead to a spectral tilt consistent with recent WMAP observations.« less

The Inflatable Poster

NASA Astrophysics Data System (ADS)

Tackley, P. J.

2004-12-01

Inflatable devices are frequently used in advertising in order to grab the attention of consumers: one sees, for example, 20 foot tall inflatable drink containers, inflatable cell phones, inflatable bubble gum packets, as well as blimps wafting majestically over major sports events. More usefully, inflatable representations of scientifically-interesting items are widely available, including astronauts, space shuttles, dinosaurs and globes and can help to build and inspire the interest of the general public, and in particular children, in such ideas. How can such concepts be adapted to improve poster presentations? Possibility one is to use relevant existing commercially-available inflatables to dress the poster: skeletons, astronauts, globes and so forth. More exciting is to develop custom inflatables that represent three-dimensional renderings of objects that the poster is describing. Examples of individual objects might be an inflatable slab, inflatable avalanche, inflatable plume, or it's larger cousin, the 10 foot high inflatable superplume or 20 foot high inflatable megaplume. More elaborately, inflatables might represent isosurfaces in three-dimensional spherical convection, although other fabrication methods may be more suitable. More simply, inflatable spheres could be imprinted with the planform of convection, geoid, or other spherical fields of geophysical interest. Finally, it should be possible to put an entire poster on an inflatable object, possibly small ones (balloons) to hand out. A major concern, however, is that the presenter may use such techniques to inflate their scientific findings, or to present overblown ideas.

The Relationship between Inflation and Inflation Uncertainty. Empirical Evidence for the Newest EU Countries

PubMed Central

Viorica, Daniela; Jemna, Danut; Pintilescu, Carmen; Asandului, Mircea

2014-01-01

The objective of this paper is to verify the hypotheses presented in the literature on the causal relationship between inflation and its uncertainty, for the newest EU countries. To ensure the robustness of the results, in the study four models for inflation uncertainty are estimated in parallel: ARCH (1), GARCH (1,1), EGARCH (1,1,1) and PARCH (1,1,1). The Granger method is used to test the causality between two variables. The working hypothesis is that groups of countries with a similar political and economic background in 1990 and are likely to be characterized by the same causal relationship between inflation and inflation uncertainty. Empirical results partially confirm this hypothesis. Jel Classification C22, E31, E37. PMID:24633073

Extended inflation from higher dimensional theories

NASA Technical Reports Server (NTRS)

Holman, Richard; Kolb, Edward W.; Vadas, Sharon L.; Wang, Yun

1990-01-01

The possibility is considered that higher dimensional theories may, upon reduction to four dimensions, allow extended inflation to occur. Two separate models are analayzed. One is a very simple toy model consisting of higher dimensional gravity coupled to a scalar field whose potential allows for a first-order phase transition. The other is a more sophisticated model incorporating the effects of non-trivial field configurations (monopole, Casimir, and fermion bilinear condensate effects) that yield a non-trivial potential for the radius of the internal space. It was found that extended inflation does not occur in these models. It was also found that the bubble nucleation rate in these theories is time dependent unlike the case in the original version of extended inflation.

Stability issues of nonlocal gravity during primordial inflation

NASA Astrophysics Data System (ADS)

Belgacem, Enis; Cusin, Giulia; Foffa, Stefano; Maggiore, Michele; Mancarella, Michele

2018-01-01

We study the cosmological evolution of some nonlocal gravity models, when the initial conditions are set during a phase of primordial inflation. We examine in particular three models, the so-called RT, RR and Δ4 models, previously introduced by our group. We find that, during inflation, the RT model has a viable background evolution, but at the level of cosmological perturbations develops instabilities that make it nonviable. In contrast, the RR and Δ4 models have a viable evolution even when their initial conditions are set during a phase of primordial inflation.

Zero-Inertial Recession for a Kinematic Wave Model

USDA-ARS?s Scientific Manuscript database

Kinematic-wave models of surface irrigation assume a fixed relationship between depth and discharge (typically, normal depth). When surface irrigation inflow is cut off, the calculated upstream flow depth goes to zero, since the discharge is zero. For short time steps, use of the Kinematic Wave mode...

Generic analysis of kinetically driven inflation

NASA Astrophysics Data System (ADS)

Saitou, Rio

2018-04-01

We perform a model-independent analysis of kinetically driven inflation (KDI) which (partially) includes generalized G-inflation and ghost inflation. We evaluate the background evolution splitting into the inflationary attractor and the perturbation around it. We also consider the quantum fluctuation of the scalar mode with a usual scaling and derive the spectral index, ignoring the contribution from the second-order products of slow-roll parameters. Using these formalisms, we find that within our generic framework the models of KDI which possess the shift symmetry of scalar field cannot create the quantum fluctuation consistent with the observation. Breaking the shift symmetry, we obtain a few essential conditions for viable models of KDI associated with the graceful exit.

Inflatable Dark Matter

DOE PAGES

Davoudiasl, Hooman; Hooper, Dan; McDermott, Samuel D.

2016-01-22

We describe a general scenario, dubbed “Inflatable Dark Matter”, in which the density of dark matter particles can be reduced through a short period of late-time inflation in the early universe. The overproduction of dark matter that is predicted within many otherwise well-motivated models of new physics can be elegantly remedied within this context, without the need to tune underlying parameters or to appeal to anthropic considerations. Thermal relics that would otherwise be disfavored can easily be accommodated within this class of scenarios, including dark matter candidates that are very heavy or very light. Furthermore, the non-thermal abundance of GUTmore » or Planck scale axions can be brought to acceptable levels, without invoking anthropic tuning of initial conditions. Additionally, a period of late-time inflation could have occurred over a wide range of scales from ~ MeV to the weak scale or above, and could have been triggered by physics within a hidden sector, with small but not necessarily negligible couplings to the Standard Model.« less

Constraints on single-field inflation

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

Pirtskhalava, David; Santoni, Luca; Trincherini, Enrico

2016-06-28

Many alternatives to canonical slow-roll inflation have been proposed over the years, one of the main motivations being to have a model, capable of generating observable values of non-Gaussianity. In this work, we (re-)explore the physical implications of a great majority of such models within a single, effective field theory framework (including novel models with large non-Gaussianity discussed for the first time below). The constraints we apply — both theoretical and experimental — are found to be rather robust, determined to a great extent by just three parameters: the coefficients of the quadratic EFT operators (δN){sup 2} and δNδE, andmore » the slow-roll parameter ε. This allows to significantly limit the majority of single-field alternatives to canonical slow-roll inflation. While the existing data still leaves some room for most of the considered models, the situation would change dramatically if the current upper limit on the tensor-to-scalar ratio decreased down to r<10{sup −2}. Apart from inflationary models driven by plateau-like potentials, the single-field model that would have a chance of surviving this bound is the recently proposed slow-roll inflation with weakly-broken galileon symmetry. In contrast to canonical slow-roll inflation, the latter model can support r<10{sup −2} even if driven by a convex potential, as well as generate observable values for the amplitude of non-Gaussianity.« less

Attractor behaviour in multifield inflation

NASA Astrophysics Data System (ADS)

Carrilho, Pedro; Mulryne, David; Ronayne, John; Tenkanen, Tommi

2018-06-01

We study multifield inflation in scenarios where the fields are coupled non-minimally to gravity via ξI(phiI)n gμνRμν, where ξI are coupling constants, phiI the fields driving inflation, gμν the space-time metric, Rμν the Ricci tensor, and n>0. We consider the so-called α-attractor models in two formulations of gravity: in the usual metric case where Rμν=Rμν(gμν), and in the Palatini formulation where Rμν is an independent variable. As the main result, we show that, regardless of the underlying theory of gravity, the field-space curvature in the Einstein frame has no influence on the inflationary dynamics at the limit of large ξI, and one effectively retains the single-field case. However, the gravity formulation does play an important role: in the metric case the result means that multifield models approach the single-field α-attractor limit, whereas in the Palatini case the attractor behaviour is lost also in the case of multifield inflation. We discuss what this means for distinguishing between different models of inflation.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots.

PubMed

Washington, Simon; Haque, Md Mazharul; Oh, Jutaek; Lee, Dongmin

2014-05-01

Hot spot identification (HSID) aims to identify potential sites-roadway segments, intersections, crosswalks, interchanges, ramps, etc.-with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

NASA Astrophysics Data System (ADS)

Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

2018-01-01

Statistical downscaling models (SDMs) are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

Evaluating Differential Effects Using Regression Interactions and Regression Mixture Models

ERIC Educational Resources Information Center

Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

2015-01-01

Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their…

Low-Mass Inflation Systems for Inflatable Structures

NASA Technical Reports Server (NTRS)

Thunnissen, Daniel P.; Webster, Mark S.; Engelbrecht, Carl S.

1995-01-01

The use of inflatable space structures has often been proposed for aerospace and planetary applications. Communication, power generation, and very-long-baseline interferometry are just three potential applications of inflatable technology. The success of inflatable structures depends on the development of an applications of inflatable technology. This paper describes two design studies performed to develop a low mass inflation system. The first study takes advantage of existing onboard propulsion gases to reduce the overall system mass. The second study assumes that there is no onboard propulsion system. Both studies employ advanced components developed for the Pluto fast flyby spacecraft to further reduce mass. The study examined four different types of systems: hydrazine, nitrogen and water, nitrogen, and xenon. This study shows that all of these systems can be built for a small space structure with masses lower than 0.5 kilograms.

Inflation in a closed universe

NASA Astrophysics Data System (ADS)

Ratra, Bharat

2017-11-01

To derive a power spectrum for energy density inhomogeneities in a closed universe, we study a spatially-closed inflation-modified hot big bang model whose evolutionary history is divided into three epochs: an early slowly-rolling scalar field inflation epoch and the usual radiation and nonrelativistic matter epochs. (For our purposes it is not necessary to consider a final dark energy dominated epoch.) We derive general solutions of the relativistic linear perturbation equations in each epoch. The constants of integration in the inflation epoch solutions are determined from de Sitter invariant quantum-mechanical initial conditions in the Lorentzian section of the inflating closed de Sitter space derived from Hawking's prescription that the quantum state of the universe only include field configurations that are regular on the Euclidean (de Sitter) sphere section. The constants of integration in the radiation and matter epoch solutions are determined from joining conditions derived by requiring that the linear perturbation equations remain nonsingular at the transitions between epochs. The matter epoch power spectrum of gauge-invariant energy density inhomogeneities is not a power law, and depends on spatial wave number in the way expected for a generalization to the closed model of the standard flat-space scale-invariant power spectrum. The power spectrum we derive appears to differ from a number of other closed inflation model power spectra derived assuming different (presumably non de Sitter invariant) initial conditions.

New type of hill-top inflation

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

Barvinsky, A.O.; Department of Physics, Tomsk State University,Lenin Ave. 36, Tomsk 634050; Department of Physics and Astronomy, Pacific Institue for Theoretical Physics,University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1

2016-01-20

We suggest a new type of hill-top inflation originating from the initial conditions in the form of the microcanonical density matrix for the cosmological model with a large number of quantum fields conformally coupled to gravity. Initial conditions for inflation are set up by cosmological instantons describing underbarrier oscillations in the vicinity of the inflaton potential maximum. These periodic oscillations of the inflaton field and cosmological scale factor are obtained within the approximation of two coupled oscillators subject to the slow roll regime in the Euclidean time. This regime is characterized by rapid oscillations of the scale factor on themore » background of a slowly varying inflaton, which guarantees smallness of slow roll parameters ϵ and η of the following inflation stage. A hill-like shape of the inflaton potential is shown to be generated by logarithmic loop corrections to the tree-level asymptotically shift-invariant potential in the non-minimal Higgs inflation model and R{sup 2}-gravity. The solution to the problem of hierarchy between the Planckian scale and the inflation scale is discussed within the concept of conformal higher spin fields, which also suggests the mechanism bringing the model below the gravitational cutoff and, thus, protecting it from large graviton loop corrections.« less

New type of hill-top inflation

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

Barvinsky, A.O.; Nesterov, D.V.; Kamenshchik, A.Yu., E-mail: barvin@td.lpi.ru, E-mail: Alexander.Kamenshchik@bo.infn.it, E-mail: nesterov@td.lpi.ru

2016-01-01

We suggest a new type of hill-top inflation originating from the initial conditions in the form of the microcanonical density matrix for the cosmological model with a large number of quantum fields conformally coupled to gravity. Initial conditions for inflation are set up by cosmological instantons describing underbarrier oscillations in the vicinity of the inflaton potential maximum. These periodic oscillations of the inflaton field and cosmological scale factor are obtained within the approximation of two coupled oscillators subject to the slow roll regime in the Euclidean time. This regime is characterized by rapid oscillations of the scale factor on themore » background of a slowly varying inflaton, which guarantees smallness of slow roll parameters ε and η of the following inflation stage. A hill-like shape of the inflaton potential is shown to be generated by logarithmic loop corrections to the tree-level asymptotically shift-invariant potential in the non-minimal Higgs inflation model and R{sup 2}-gravity. The solution to the problem of hierarchy between the Planckian scale and the inflation scale is discussed within the concept of conformal higher spin fields, which also suggests the mechanism bringing the model below the gravitational cutoff and, thus, protecting it from large graviton loop corrections.« less

LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies

PubMed Central

Bulik-Sullivan, Brendan K.; Loh, Po-Ru; Finucane, Hilary; Ripke, Stephan; Yang, Jian; Patterson, Nick; Daly, Mark J.; Price, Alkes L.; Neale, Benjamin M.

2015-01-01

Both polygenicity (i.e., many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size. PMID:25642630

Negative running can prevent eternal inflation

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

Kinney, William H.; Freese, Katherine, E-mail: whkinney@buffalo.edu, E-mail: ktfreese@umich.edu

Current data from the Planck satellite and the BICEP2 telescope favor, at around the 2 σ level, negative running of the spectral index of curvature perturbations from inflation. We show that for negative running α < 0, the curvature perturbation amplitude has a maximum on scales larger than our current horizon size. A condition for the absence of eternal inflation is that the curvature perturbation amplitude always remain below unity on superhorizon scales. For current bounds on n{sub S} from Planck, this corresponds to an upper bound of the running α < −9 × 10{sup −5}, so that even tiny running of the scalar spectral index ismore » sufficient to prevent eternal inflation from occurring, as long as the running remains negative on scales outside the horizon. In single-field inflation models, negative running is associated with a finite duration of inflation: we show that eternal inflation may not occur even in cases where inflation lasts as long as 10{sup 4} e-folds.« less

Issues on generating primordial anisotropies at the end of inflation

NASA Astrophysics Data System (ADS)

Emami, Razieh; Firouzjahi, Hassan

2012-01-01

We revisit the idea of generating primordial anisotropies at the end of inflation in models of inflation with gauge fields. To be specific we consider the charged hybrid inflation model where the waterfall field is charged under a U(1) gauge field so the surface of end of inflation is controlled both by inflaton and the gauge fields. Using δN formalism properly we find that the anisotropies generated at the end of inflation from the gauge field fluctuations are exponentially suppressed on cosmological scales. This is because the gauge field evolves exponentially during inflation while in order to generate appreciable anisotropies at the end of inflation the spectator gauge field has to be frozen. We argue that this is a generic feature, that is, one can not generate observable anisotropies at the end of inflation within an FRW background.

Inflatable Structures Technology Handbook. Chapter 21; Inflatable Habitats

NASA Technical Reports Server (NTRS)

Kennedy, Kriss J.; Raboin, Jasen; Spexarth, Gary; Valle, Gerard

2000-01-01

The technologies required to design, fabricate, and utilize an inflatable module for space applications has been demonstrated and proven by the TransHab team during the development phase of the program. Through testing and hands-on development several issues about inflatable space structures have been addressed , such as: ease of manufacturing, structural integrity, micrometeorite protection, folding , and vacuum deployment. The TransHab inflatable technology development program has proven that not only are inflatable structures a viable option, but they also offer significant advantages over conventional metallic structures.

RE-INFLATED WARM JUPITERS AROUND RED GIANTS

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

Lopez, Eric D.; Fortney, Jonathan J.

2016-02-10

Since the discovery of the first transiting hot Jupiters, models have sought to explain the anomalously large radii of highly irradiated gas giants. We now know that the size of hot Jupiter radius anomalies scales strongly with a planet's level of irradiation and numerous models like tidal heating, ohmic dissipation, and thermal tides have since been developed to help explain these inflated radii. In general, however, these models can be grouped into two broad categories: models that directly inflate planetary radii by depositing a fraction of the incident irradiation into the interior and models that simply slow a planet's radiativemore » cooling, allowing it to retain more heat from formation and thereby delay contraction. Here we present a new test to distinguish between these two classes of models. Gas giants orbiting at moderate orbital periods around post-main-sequence stars will experience enormous increases to their irradiation as their host stars move up the sub-giant and red-giant branches. If hot Jupiter inflation works by depositing irradiation into the planet's deep interiors then planetary radii should increase in response to the increased irradiation. This means that otherwise non-inflated gas giants at moderate orbital periods of >10 days can re-inflate as their host stars evolve. Here we explore the circumstances that can lead to the creation of these “re-inflated” gas giants and examine how the existence or absence of such planets can be used to place unique constraints on the physics of the hot Jupiter inflation mechanism. Finally, we explore the prospects for detecting this potentially important undiscovered population of planets.« less

Cosmic Inflation

ScienceCinema

Lincoln, Don

2018-01-16

In 1964, scientists discovered a faint radio hiss coming from the heavens and realized that the hiss wasn’t just noise. It was a message from eons ago; specifically the remnants of the primordial fireball, cooled to about 3 degrees above absolute zero. Subsequent research revealed that the radio hiss was the same in every direction. The temperature of the early universe was uniform to at better than a part in a hundred thousand. And this was weird. According to the prevailing theory, the two sides of the universe have never been in contact. So how could two places that had never been in contact be so similar? One possible explanation was proposed in 1979. Called inflation, the theory required that early in the history of the universe, the universe expanded faster than the speed of light. Confused? Watch this video as Fermilab’s Dr. Don Lincoln makes sense of this mind-bending idea.

Cosmic Inflation

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

Lincoln, Don

In 1964, scientists discovered a faint radio hiss coming from the heavens and realized that the hiss wasn’t just noise. It was a message from eons ago; specifically the remnants of the primordial fireball, cooled to about 3 degrees above absolute zero. Subsequent research revealed that the radio hiss was the same in every direction. The temperature of the early universe was uniform to at better than a part in a hundred thousand. And this was weird. According to the prevailing theory, the two sides of the universe have never been in contact. So how could two places that hadmore » never been in contact be so similar? One possible explanation was proposed in 1979. Called inflation, the theory required that early in the history of the universe, the universe expanded faster than the speed of light. Confused? Watch this video as Fermilab’s Dr. Don Lincoln makes sense of this mind-bending idea.« less

Unitarity and predictiveness in new Higgs inflation

NASA Astrophysics Data System (ADS)

Fumagalli, Jacopo; Mooij, Sander; Postma, Marieke

2018-03-01

In new Higgs inflation the Higgs kinetic terms are non-minimally coupled to the Einstein tensor, allowing the Higgs field to play the role of the inflaton. The new interaction is non-renormalizable, and the model only describes physics below some cutoff scale. Even if the unknown UV physics does not affect the tree level inflaton potential significantly, it may still enter at loop level and modify the running of the Standard Model (SM) parameters. This is analogous to what happens in the original model for Higgs inflation. A key difference, though, is that in new Higgs inflation the inflationary predictions are sensitive to this running. Thus the boundary conditions at the EW scale as well as the unknown UV completion may leave a signature on the inflationary parameters. However, this dependence can be evaded if the kinetic terms of the SM fermions and gauge fields are non-minimally coupled to gravity as well. Our approach to determine the model's UV dependence and the connection between low and high scale physics can be used in any particle physics model of inflation.

Goldstone inflation

NASA Astrophysics Data System (ADS)

Croon, Djuna; Sanz, Verónica; Setford, Jack

2015-10-01

Identifying the inflaton with a pseudo-Goldstone boson explains the flatness of its potential. Successful Goldstone Inflation should also be robust against UV corrections, such as from quantum gravity: in the language of the effective field theory this implies that all scales are sub-Planckian. In this paper we present scenarios which realise both requirements by examining the structure of Goldstone potentials arising from Coleman-Weinberg contributions. We focus on single-field models, for which we notice that both bosonic and fermionic contributions are required and that spinorial fermion representations can generate the right potential shape. We then evaluate the constraints on non-Gaussianity from higher-derivative interactions, finding that axiomatic constraints on Goldstone boson scattering prevail over the current CMB measurements. The fit to CMB data can be connected to the UV completions for Goldstone Inflation, finding relations in the spectrum of new resonances. Finally, we show how hybrid inflation can be realised in the same context, where both the inflaton and the waterfall fields share a common origin as Goldstones.

Supernatural A-Term Inflation

NASA Astrophysics Data System (ADS)

Lin, Chia-Min; Cheung, Kingman

Following Ref. 10, we explore the parameter space of the case when the supersymmetry (SUSY) breaking scale is lower, for example, in gauge mediated SUSY breaking model. During inflation, the form of the potential is V0 plus MSSM (or A-term) inflation. We show that the model works for a wide range of the potential V0 with the soft SUSY breaking mass m O(1) TeV. The implication to MSSM (or A-term) inflation is that the flat directions which is lifted by the non-renormalizable terms described by the superpotential W=λ p φ p-1/Mp-3 P with p = 4 and p = 5 are also suitable to be an inflaton field for λp = O(1) provided there is an additional false vacuum term V0 with appropriate magnitude. The flat directions correspond to p = 6 also works for 0 < ˜ V0/M_ P4 < ˜ 10-40.

Survival Data and Regression Models

NASA Astrophysics Data System (ADS)

Grégoire, G.

2014-12-01

We start this chapter by introducing some basic elements for the analysis of censored survival data. Then we focus on right censored data and develop two types of regression models. The first one concerns the so-called accelerated failure time models (AFT), which are parametric models where a function of a parameter depends linearly on the covariables. The second one is a semiparametric model, where the covariables enter in a multiplicative form in the expression of the hazard rate function. The main statistical tool for analysing these regression models is the maximum likelihood methodology and, in spite we recall some essential results about the ML theory, we refer to the chapter "Logistic Regression" for a more detailed presentation.

Analysis of multinomial models with unknown index using data augmentation

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, R.M.; Link, W.A.

2007-01-01

Multinomial models with unknown index ('sample size') arise in many practical settings. In practice, Bayesian analysis of such models has proved difficult because the dimension of the parameter space is not fixed, being in some cases a function of the unknown index. We describe a data augmentation approach to the analysis of this class of models that provides for a generic and efficient Bayesian implementation. Under this approach, the data are augmented with all-zero detection histories. The resulting augmented dataset is modeled as a zero-inflated version of the complete-data model where an estimable zero-inflation parameter takes the place of the unknown multinomial index. Interestingly, data augmentation can be justified as being equivalent to imposing a discrete uniform prior on the multinomial index. We provide three examples involving estimating the size of an animal population, estimating the number of diabetes cases in a population using the Rasch model, and the motivating example of estimating the number of species in an animal community with latent probabilities of species occurrence and detection.

Inflation and Growth: Positive or Negative Relationship?

NASA Astrophysics Data System (ADS)

Berument, Hakan; Inamlik, Ali; Olgun, Hasan

This study has been motivated by two developments. Firstly, by the vast literature on the relationship between inflation and growth which is abundantly endowed with diverse theoretical explanations and contradictory evidence and by the unique experience of the Turkish economy with inflation and growth. A preliminary examination of the Turkish data pointed to a negative relation between inflation and growth. Moreover, there is a unanimous agreement among the students of the Turkish economy that many factors have contributed to inflation in this country. In view of these facts this paper employs a VAR model which will enable us to identify the sources of the shocks and control for external factors. In addition VAR models have a high predictive power and enable the researcher to observe the impulse response functions. The study employs Generalised Impulse Response analysis. In the empirical experiments oil prices, money supply, government spending and taxes have been taken as the most likely determinants of inflation. The study shows that there is a negative relationship between inflation and output growth in Turkey and that the underlying explanatory factor is the real exchange rate. This result is robust.

Clockwork inflation

NASA Astrophysics Data System (ADS)

Kehagias, Alex; Riotto, Antonio

2017-04-01

We investigate the recently proposed clockwork mechanism delivering light degrees of freedom with suppressed interactions and show, with various examples, that it can be efficiently implemented in inflationary scenarios to generate flat inflaton potentials and small density perturbations without fine-tunings. We also study the clockwork graviton in de Sitter and, interestingly, we find that the corresponding clockwork charge is site-dependent. As a consequence, the amount of tensor modes is generically suppressed with respect to the standard cases where the clockwork set-up is not adopted. This point can be made a virtue in resurrecting models of inflation which were supposed to be ruled out because of the excessive amount of tensor modes from inflation.

New Old Inflation

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

Dvali, Gia

2003-10-03

We propose a new class of inflationary solutions to the standard cosmological problems (horizon, flatness, monopole,...), based on a modification of old inflation. These models do not require a potential which satisfies the normal inflationary slow-roll conditions. Our universe arises from a single tunneling event as the inflaton leaves the false vacuum. Subsequent dynamics (arising from either the oscillations of the inflaton field or thermal effects) keep a second field trapped in a false minimum, resulting in an evanescent period of inflation (with roughly 50 e-foldings) inside the bubble. This easily allows the bubble to grow sufficiently large to containmore » our present horizon volume. Reheating is accomplished when the inflaton driving the last stage of inflation rolls down to the true vacuum, and adiabatic density perturbations arise from moduli-dependent Yukawa couplings of the inflaton to matter fields. Our scenario has several robust predictions, including virtual absence of gravity waves, a possible absence of tilt in scalar perturbations, and a higher degree of non-Gaussianity than other models. It also naturally incorporates a solution to the cosmological moduli problem.« less

Overall Preference of Running Shoes Can Be Predicted by Suitable Perception Factors Using a Multiple Regression Model.

PubMed

Tay, Cheryl Sihui; Sterzing, Thorsten; Lim, Chen Yen; Ding, Rui; Kong, Pui Wah

2017-05-01

This study examined (a) the strength of four individual footwear perception factors to influence the overall preference of running shoes and (b) whether these perception factors satisfied the nonmulticollinear assumption in a regression model. Running footwear must fulfill multiple functional criteria to satisfy its potential users. Footwear perception factors, such as fit and cushioning, are commonly used to guide shoe design and development, but it is unclear whether running-footwear users are able to differentiate one factor from another. One hundred casual runners assessed four running shoes on a 15-cm visual analogue scale for four footwear perception factors (fit, cushioning, arch support, and stability) as well as for overall preference during a treadmill running protocol. Diagnostic tests showed an absence of multicollinearity between factors, where values for tolerance ranged from .36 to .72, corresponding to variance inflation factors of 2.8 to 1.4. The multiple regression model of these four footwear perception variables accounted for 77.7% to 81.6% of variance in overall preference, with each factor explaining a unique part of the total variance. Casual runners were able to rate each footwear perception factor separately, thus assigning each factor a true potential to improve overall preference for the users. The results also support the use of a multiple regression model of footwear perception factors to predict overall running shoe preference. Regression modeling is a useful tool for running-shoe manufacturers to more precisely evaluate how individual factors contribute to the subjective assessment of running footwear.

Fisher zeros and conformality in lattice models

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

Meurice, Yannick; Bazavov, Alexei; Berg, Bernd A.

2012-10-01

Fisher zeros are the zeros of the partition function in the complex beta=2N_c/g^2 plane. When they pinch the real axis, finite size scaling allows one to distinguish between first and second order transition and to estimate exponents. On the other hand, a gap signals confinement and the method can be used to explore the boundary of the conformal window. We present recent numerical results for 2D O(N) sigma models, 4D U(1) and SU(2) pure gauge and SU(3) gauge theory with N_f=4 and 12 flavors. We discuss attempts to understand some of these results using analytical methods. We discuss the 2-latticemore » matching and qualitative aspects of the renormalization group (RG) flows in the Migdal-Kadanoff approximation, in particular how RG flows starting at large beta seem to move around regions where bulk transitions occur. We consider the effects of the boundary conditions on the nonperturbative part of the average energy and on the Fisher zeros for the 1D O(2) model.« less

Deflation of the cosmological constant associated with inflation and dark energy

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

Geng, Chao-Qiang; Lee, Chung-Chi, E-mail: geng@phys.nthu.edu.tw, E-mail: chungchi@mx.nthu.edu.tw

2016-06-01

In order to solve the fine-tuning problem of the cosmological constant, we propose a simple model with the vacuum energy non-minimally coupled to the inflaton field. In this model, the vacuum energy decays to the inflaton during pre-inflation and inflation eras, so that the cosmological constant effectively deflates from the Planck mass scale to a much smaller one after inflation and plays the role of dark energy in the late-time of the universe. We show that our deflationary scenario is applicable to arbitrary slow-roll inflation models. We also take two specific inflation potentials to illustrate our results.

Cytomegalovirus Reinfections Stimulate CD8 T-Memory Inflation.

PubMed

Trgovcich, Joanne; Kincaid, Michelle; Thomas, Alicia; Griessl, Marion; Zimmerman, Peter; Dwivedi, Varun; Bergdall, Valerie; Klenerman, Paul; Cook, Charles H

2016-01-01

Cytomegalovirus (CMV) has been shown to induce large populations of CD8 T-effector memory cells that unlike central memory persist in large quantities following infection, a phenomenon commonly termed "memory inflation". Although murine models to date have shown very large and persistent CMV-specific T-cell expansions following infection, there is considerable variability in CMV-specific T-memory responses in humans. Historically such memory inflation in humans has been assumed a consequence of reactivation events during the life of the host. Because basic information about CMV infection/re-infection and reactivation in immune competent humans is not available, we used a murine model to test how primary infection, reinfection, and reactivation stimuli influence memory inflation. We show that low titer infections induce "partial" memory inflation of both mCMV specific CD8 T-cells and antibody. We show further that reinfection with different strains can boost partial memory inflation. Finally, we show preliminary results suggesting that a single strong reactivation stimulus does not stimulate memory inflation. Altogether, our results suggest that while high titer primary infections can induce memory inflation, reinfections during the life of a host may be more important than previously appreciated.

Intermediate inflation from a non-canonical scalar field

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

Rezazadeh, K.; Karami, K.; Karimi, P., E-mail: rezazadeh86@gmail.com, E-mail: KKarami@uok.ac.ir, E-mail: parvin.karimi67@yahoo.com

2015-09-01

We study the intermediate inflation in a non-canonical scalar field framework with a power-like Lagrangian. We show that in contrast with the standard canonical intermediate inflation, our non-canonical model is compatible with the observational results of Planck 2015. Also, we estimate the equilateral non-Gaussianity parameter which is in well agreement with the prediction of Planck 2015. Then, we obtain an approximation for the energy scale at the initial time of inflation and show that it can be of order of the Planck energy scale, i.e. M{sub P} ∼ 10{sup 18}GeV. We will see that after a short period of time, inflation entersmore » in the slow-roll regime that its energy scale is of order M{sub P}/100 ∼ 10{sup 16}GeV and the horizon exit takes place in this energy scale. We also examine an idea in our non-canonical model to overcome the central drawback of intermediate inflation which is the fact that inflation never ends. We solve this problem without disturbing significantly the nature of the intermediate inflation until the time of horizon exit.« less

Evading the Lyth bound in hybrid natural inflation

NASA Astrophysics Data System (ADS)

Hebecker, A.; Kraus, S. C.; Westphal, A.

2013-12-01

Generically, the gravitational-wave or tensor-mode contribution to the primordial curvature spectrum of inflation is tiny if the field range of the inflaton is much smaller than the Planck scale. We show that this pessimistic conclusion is naturally avoided in a rather broad class of small-field models. More specifically, we consider models where an axionlike shift symmetry keeps the inflaton potential flat (up to nonperturbative cosine-shaped modulations), but inflation nevertheless ends in a waterfall regime, as is typical for hybrid inflation. In such hybrid natural inflation scenarios (examples are provided by Wilson line inflation and fluxbrane inflation), the slow-roll parameter ɛ can be sizable during an early period (relevant for the cosmic microwave background spectrum). Subsequently, ɛ quickly becomes very small before the tachyonic instability eventually terminates the slow-roll regime. In this scenario, one naturally generates a considerable tensor-mode contribution in the curvature spectrum, collecting nevertheless the required amount of e-foldings during the final period of inflation. While nonobservation of tensors by Planck is certainly not a problem, a discovery in the medium- to long-term future is realistic.

Quantile regression applied to spectral distance decay

USGS Publications Warehouse

Rocchini, D.; Cade, B.S.

2008-01-01

Remotely sensed imagery has long been recognized as a powerful support for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance allows us to quantitatively estimate the amount of turnover in species composition with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological data sets are characterized by a high number of zeroes that add noise to the regression model. Quantile regressions can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this letter, we used ordinary least squares (OLS) and quantile regressions to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.01), considering both OLS and quantile regressions. Nonetheless, the OLS regression estimate of the mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when the spectral distance approaches zero, was very low compared with the intercepts of the upper quantiles, which detected high species similarity when habitats are more similar. In this letter, we demonstrated the power of using quantile regressions applied to spectral distance decay to reveal species diversity patterns otherwise lost or underestimated by OLS regression. ?? 2008 IEEE.

Reheating-volume measure for random-walk inflation

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

Winitzki, Sergei; Yukawa Institute of Theoretical Physics, Kyoto University, Kyoto

2008-09-15

The recently proposed 'reheating-volume' (RV) measure promises to solve the long-standing problem of extracting probabilistic predictions from cosmological multiverse scenarios involving eternal inflation. I give a detailed description of the new measure and its applications to generic models of eternal inflation of random-walk type. For those models I derive a general formula for RV-regulated probability distributions that is suitable for numerical computations. I show that the results of the RV cutoff in random-walk type models are always gauge invariant and independent of the initial conditions at the beginning of inflation. In a toy model where equal-time cutoffs lead to themore » 'youngness paradox', the RV cutoff yields unbiased results that are distinct from previously proposed measures.« less

Gravitational waves and large field inflation

NASA Astrophysics Data System (ADS)

Linde, Andrei

2017-02-01

According to the famous Lyth bound, one can confirm large field inflation by finding tensor modes with sufficiently large tensor-to-scalar ratio r. Here we will try to answer two related questions: is it possible to rule out all large field inflationary models by not finding tensor modes with r above some critical value, and what can we say about the scale of inflation by measuring r? However, in order to answer these questions one should distinguish between two different definitions of the large field inflation and three different definitions of the scale of inflation. We will examine these issues using the theory of cosmological α-attractors as a convenient testing ground.

Leptogenesis from gravity waves in models of inflation.

PubMed

Alexander, Stephon H S; Peskin, Michael E; Sheikh-Jabbari, M M

2006-03-03

We present a new mechanism for creating the observed cosmic matter-antimatter asymmetry which satisfies all three Sakharov conditions from one common thread, gravitational waves. We generate lepton number through the gravitational anomaly in the lepton number current. The source term comes from elliptically polarized gravity waves that are produced during inflation if the inflaton field contains a CP-odd component. The amount of matter asymmetry generated in our model can be of realistic size for the parameters within the range of some inflationary scenarios and grand unified theories.

Pati-Salam version of subcritical hybrid inflation

NASA Astrophysics Data System (ADS)

Bryant, B. Charles; Raby, Stuart

2016-05-01

In this paper we present a model of subcritical hybrid inflation with a Pati-Salam (PS) symmetry group. Both the inflaton and waterfall fields contribute to the necessary e -foldings of inflation, while only the waterfall field spontaneously breaks PS hence monopoles produced during inflation are diluted during the inflationary epoch. The model is able to produce a tensor-to-scalar ratio, r <0.09 consistent with the latest BICEP2/Keck and Planck data, as well as scalar density perturbations and spectral index, ns, consistent with Planck data. For particular values of the parameters, we find r =0.084 and ns=0.0963 . The energy density during inflation is directly related to the PS breaking scale, vPS. The model also incorporates a Z4R symmetry which can resolve the μ problem and suppress dimension 5 operators for proton decay, leaving over an exact R parity. Finally the model allows for a complete three-family extension with a D4 family symmetry which reproduces low energy precision electroweak and LHC data.

Interpretation of commonly used statistical regression models.

PubMed

Kasza, Jessica; Wolfe, Rory

2014-01-01

A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

Does the first chaotic inflation model in supergravity provide the best fit to the Planck data?

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

Linde, Andrei

2015-02-23

I describe the first model of chaotic inflation in supergravity, which was proposed by Goncharov and the present author in 1983. The inflaton potential of this model has a plateau-type behavior V{sub 0}(1−(8/3) e{sup −√6|ϕ|}) at large values of the inflaton field. This model predicts n{sub s}=1−(2/N)≈0.967 and r=(4/(3N{sup 2}))≈4×10{sup −4}, in good agreement with the Planck data. I propose a slight generalization of this model, which allows to describe not only inflation but also dark energy and supersymmetry breaking.

Development of Inflatable Entry Systems Technologies

NASA Technical Reports Server (NTRS)

Player, Charles J.; Cheatwood, F. McNeil; Corliss, James

2005-01-01

Achieving the objectives of NASA s Vision for Space Exploration will require the development of new technologies, which will in turn require higher fidelity modeling and analysis techniques, and innovative testing capabilities. Development of entry systems technologies can be especially difficult due to the lack of facilities and resources available to test these new technologies in mission relevant environments. This paper discusses the technology development process to bring inflatable aeroshell technology from Technology Readiness Level 2 (TRL-2) to TRL-7. This paper focuses mainly on two projects: Inflatable Reentry Vehicle Experiment (IRVE), and Inflatable Aeroshell and Thermal Protection System Development (IATD). The objectives of IRVE are to conduct an inflatable aeroshell flight test that demonstrates exoatmospheric deployment and inflation, reentry survivability and stability, and predictable drag performance. IATD will continue the development of the technology by conducting exploration specific trade studies and feeding forward those results into three more flight tests. Through an examination of these projects, and other potential projects, this paper discusses some of the risks, issues, and unexpected benefits associated with the development of inflatable entry systems technology.

Structural testing and analysis of a braided, inflatable fabric torus structure

NASA Astrophysics Data System (ADS)

Young, Andrew C.; Davids, William G.; Whitney, Daniel J.; Clapp, Joshua D.; Goupee, Andrew J.

2017-10-01

Inflatable structural members have military, disaster relief, aerospace and other important applications as they possess low mass, can be stored in a relatively small volume and have significant load-carrying capacity once pressurized. Of particular interest to the present research is the Hypersonic Inflatable Aerodynamic Decelerator (HIAD) structure under development by NASA. In order to make predictions about the structural response of the HIAD system, it is necessary to understand the response of individual inflatable tori composing the HIAD structure. These inflatable members present unique challenges to structural testing and modeling due to their internal inflation pressure and relative compliance. Structural testing was performed on a braided, inflatable, toroidal structural member with axial reinforcing cords. The internal inflation pressure, magnitude of enforced displacement and loading methodology were varied. In-plane and out-of-plane experimental results were compared to model predictions using a three dimensional, corotational, flexibility-based fiber-beam finite element model including geometric and material nonlinearities, as well as the effects of inflation pressure. It was found that in order to approximate the load-deformation response observed in experimentation it is necessary to carefully control the test and model boundary conditions and loading scheme.

Observational constraints on Tachyon and DBI inflation

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

Li, Sheng; Liddle, Andrew R., E-mail: sl277@sussex.ac.uk, E-mail: arl@roe.ac.uk

2014-03-01

We present a systematic method for evaluation of perturbation observables in non-canonical single-field inflation models within the slow-roll approximation, which allied with field redefinitions enables predictions to be established for a wide range of models. We use this to investigate various non-canonical inflation models, including Tachyon inflation and DBI inflation. The Lambert W function will be used extensively in our method for the evaluation of observables. In the Tachyon case, in the slow-roll approximation the model can be approximated by a canonical field with a redefined potential, which yields predictions in better agreement with observations than the canonical equivalents. Formore » DBI inflation models we consider contributions from both the scalar potential and the warp geometry. In the case of a quartic potential, we find a formula for the observables under both non-relativistic (sound speed c{sub s}{sup 2} ∼ 1) and relativistic behaviour (c{sub s}{sup 2} || 1) of the scalar DBI inflaton. For a quadratic potential we find two branches in the non-relativistic c{sub s}{sup 2} ∼ 1 case, determined by the competition of model parameters, while for the relativistic case c{sub s}{sup 2} → 0, we find consistency with results already in the literature. We present a comparison to the latest Planck satellite observations. Most of the non-canonical models we investigate, including the Tachyon, are better fits to data than canonical models with the same potential, but we find that DBI models in the slow-roll regime have difficulty in matching the data.« less

A design pathfinder with material correlation points for inflatable systems

NASA Astrophysics Data System (ADS)

Fulcher, Jared Terrell

The incorporation of inflatable structures into aerospace systems can produce significant advantages in stowed volume to mechanical effectiveness and overall weight. Many applications of these ultra-lightweight systems are designed to precisely control internal or external surfaces, or both, to achieve desired performance. The modeling of these structures becomes complex due to the material nonlinearities inherent to the majority of construction materials used in inflatable structures. Furthermore, accurately modeling the response and behavior of the interfacing boundaries that are common to many inflatable systems will lead to better understanding of the entire class of structures. The research presented involved using nonlinear finite element simulations correlated with photogrammetry testing to develop a procedure for defining material properties for commercially available polyurethane-coated woven nylon fabric, which is representative of coated materials that have been proven materials for use in many inflatable systems. Further, the new material model was used to design and develop an inflatable pathfinder system which employs only internal pressure to control an assembly of internal membranes. This canonical inflatable system will be used for exploration and development of general understanding of efficient design methodology and analysis of future systems. Canonical structures are incorporated into the design of the phased pathfinder system to allow for more universal insight. Nonlinear finite element simulations were performed to evaluate the effect of various boundary conditions, loading configurations, and material orientations on the geometric precision of geometries representing typical internal/external surfaces commonly incorporated into inflatable pathfinder system. The response of the inflatable system to possible damage was also studied using nonlinear finite element simulations. Development of a correlated material model for analysis of the

Inflation with a constant rate of roll

NASA Astrophysics Data System (ADS)

Motohashi, Hayato; Starobinsky, Alexei A.; Yokoyama, Jun'ichi

2015-09-01

We consider an inflationary scenario where the rate of inflaton roll defined by ̈phi/H dot phi remains constant. The rate of roll is small for slow-roll inflation, while a generic rate of roll leads to the interesting case of 'constant-roll' inflation. We find a general exact solution for the inflaton potential required for such inflaton behaviour. In this model, due to non-slow evolution of background, the would-be decaying mode of linear scalar (curvature) perturbations may not be neglected. It can even grow for some values of the model parameter, while the other mode always remains constant. However, this always occurs for unstable solutions which are not attractors for the given potential. The most interesting particular cases of constant-roll inflation remaining viable with the most recent observational data are quadratic hilltop inflation (with cutoff) and natural inflation (with an additional negative cosmological constant). In these cases even-order slow-roll parameters approach non-negligible constants while the odd ones are asymptotically vanishing in the quasi-de Sitter regime.

Origin of density fluctuations in extended inflation

NASA Technical Reports Server (NTRS)

Kolb, Edward W.; Salopek, David S.; Turner, Michael S.

1990-01-01

The density fluctuations (both curvature and isocurvature) that arise due to quantum fluctuations in a simple model of extended inflation based upon the Jordan-Brans-Dicke theory are calculated. Curvature fluctuations arise due to quantum fluctuations in the Brans-Dicke field, in general have a nonscale-invariant spectrum, and can have an amplitude that is cosmologically acceptable and interesting without having to tune any coupling constant to a very small value. The density perturbations that arise due to the inflation field are subdominant. If there are other massless fields in the theory, e.g., an axion or an ilion, then isocurvature fluctuations arise in these fields too. Production of gravitational waves and the massless particles associated with excitations of the Brans-Dicke field are also discussed. Several attempts at more realistic models of extended inflation are also analyzed. The importance of the Einstein conformal frame in calculating curvature fluctuations is emphasized. When viewed in this frame, extended inflation closely resembles slow-rollover inflation with an exponential potential and the usual formula for the amplitude of curvature perturbations applies.

Inflation with a constant rate of roll

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

Motohashi, Hayato; Starobinsky, Alexei A.; Yokoyama, Jun'ichi, E-mail: motohashi@kicp.uchicago.edu, E-mail: alstar@landau.ac.ru, E-mail: yokoyama@resceu.s.u-tokyo.ac.jp

2015-09-01

We consider an inflationary scenario where the rate of inflaton roll defined by {sup ··}φ/H φ-dot remains constant. The rate of roll is small for slow-roll inflation, while a generic rate of roll leads to the interesting case of 'constant-roll' inflation. We find a general exact solution for the inflaton potential required for such inflaton behaviour. In this model, due to non-slow evolution of background, the would-be decaying mode of linear scalar (curvature) perturbations may not be neglected. It can even grow for some values of the model parameter, while the other mode always remains constant. However, this always occurs formore » unstable solutions which are not attractors for the given potential. The most interesting particular cases of constant-roll inflation remaining viable with the most recent observational data are quadratic hilltop inflation (with cutoff) and natural inflation (with an additional negative cosmological constant). In these cases even-order slow-roll parameters approach non-negligible constants while the odd ones are asymptotically vanishing in the quasi-de Sitter regime.« less

Last stand of single small field inflation

NASA Astrophysics Data System (ADS)

Bramante, Joseph; Lehman, Landon; Martin, Adam; Downes, Sean

2014-07-01

By incorporating both the tensor-to-scalar ratio and the measured value of the spectral index, we set a bound on solo small field inflation of Δϕ/mPl≥1.00√r/0.1 . Unlike previous bounds which require monotonic ɛV, |ηV|<1, and 60 e-folds of inflation, the bound remains valid for nonmonotonic ɛV, |ηV|≳1, and for inflation which occurs only over the eight e-folds which have been observed on the cosmic microwave background. The negative value of the spectral index over the observed eight e-folds is what makes the bound strong; we illustrate this by surveying single field models and finding that for r ≳0.1 and eight e-folds of inflation, there is no simple potential which reproduces observed cosmic microwave background perturbations and remains sub-Planckian. Models that are sub-Planckian after eight e-folds must be patched together with a second epoch of inflation that fills out the remaining ˜50 e-folds. This second, post-cosmic microwave background epoch is characterized by extremely small ɛV and therefore an increasing scalar power spectrum. Using the fact that large power can overabundantly produce primordial black holes, we bound the maximum energy level of the second phase of inflation.

G-warm inflation

NASA Astrophysics Data System (ADS)

Herrera, Ramón

2017-05-01

A warm inflationary universe in the context of Galileon model or G-model is studied. Under a general formalism we study the inflationary dynamics and the cosmological perturbations considering a coupling of the form G(phi,X)=g(phi) X. As a concrete example, we consider an exponential potential together with the cases in which the dissipation and Galilean coefficients are constants. Also, we study the weak regime given by the condition R<1+3gHdot phi, and the strong regime in which 1inflation, assuming the condition for warm inflation in which the temperature T>H, the conditions or the weak and strong regimes, together with the consistency relation r=r(ns) from Planck data.

Deployment Simulation Methods for Ultra-Lightweight Inflatable Structures

NASA Technical Reports Server (NTRS)

Wang, John T.; Johnson, Arthur R.

2003-01-01

Two dynamic inflation simulation methods are employed for modeling the deployment of folded thin-membrane tubes. The simulations are necessary because ground tests include gravity effects and may poorly represent deployment in space. The two simulation methods are referred to as the Control Volume (CV) method and the Arbitrary Lagrangian Eulerian (ALE) method. They are available in the LS-DYNA nonlinear dynamic finite element code. Both methods are suitable for modeling the interactions between the inflation gas and the thin-membrane tube structures. The CV method only considers the pressure induced by the inflation gas in the simulation, while the ALE method models the actual flow of the inflation gas. Thus, the transient fluid properties at any location within the tube can be predicted by the ALE method. Deployment simulations of three packaged tube models; namely coiled, Z-folded, and telescopically-folded configurations, are performed. Results predicted by both methods for the telescopically-folded configuration are correlated and computational efficiency issues are discussed.

A general framework of automorphic inflation

NASA Astrophysics Data System (ADS)

Schimmrigk, Rolf

2016-05-01

Automorphic inflation is an application of the framework of automorphic scalar field theory, based on the theory of automorphic forms and representations. In this paper the general framework of automorphic and modular inflation is described in some detail, with emphasis on the resulting stratification of the space of scalar field theories in terms of the group theoretic data associated to the shift symmetry, as well as the automorphic data that specifies the potential. The class of theories based on Eisenstein series provides a natural generalization of the model of j-inflation considered previously.

The effect of cuff presence and cuff inflation on airway pressure in a canine tracheostomy tube model.

PubMed

Wignall, Jamie R; Baines, Stephen J

2014-01-01

To evaluate the effect of cuff presence and cuff inflation on airway pressure in an inspiratory model of canine tracheostomy. Ex vivo experimental study. Cadaver tracheas from Beagle dogs were attached aborally to a vacuum. Airway pressure and flow rate was measured before and after placement of tracheostomy tubes. None. Adult uncuffed tubes and cuffed tracheostomy tubes (sizes 4, 6, 8, and 10) were placed within tracheas. Cuffs were investigated without inflation and at maximum cuff inflation. Airway pressure was measured at constant airflow rates at 30 and 60 L/min. At set flow rates, airway pressures of tracheostomy tubes were compared to the intact trachea. A size 4 uncuffed tracheostomy tube showed the lowest airway pressure and a size 4 cuffed trachestomy tube with inflation showed the highest airway pressures. For sizes 6, 8, and 10 tubes, the presence of a cuff with and without inflation significantly increased airway pressure. Inflation of a cuff always significantly increased airway pressure. Similar pressure is seen between sizes 4 and 6 uncuffed tubes. Cuffed tracheostomy tubes should not be used unless specifically indicated due to increased airway pressure. © Veterinary Emergency and Critical Care Society 2013.

Power suppression at large scales in string inflation

NASA Astrophysics Data System (ADS)

Cicoli, Michele; Downes, Sean; Dutta, Bhaskar

2013-12-01

We study a possible origin of the anomalous suppression of the power spectrum at large angular scales in the cosmic microwave background within the framework of explicit string inflationary models where inflation is driven by a closed string modulus parameterizing the size of the extra dimensions. In this class of models the apparent power loss at large scales is caused by the background dynamics which involves a sharp transition from a fast-roll power law phase to a period of Starobinsky-like slow-roll inflation. An interesting feature of this class of string inflationary models is that the number of e-foldings of inflation is inversely proportional to the string coupling to a positive power. Therefore once the string coupling is tuned to small values in order to trust string perturbation theory, enough e-foldings of inflation are automatically obtained without the need of extra tuning. Moreover, in the less tuned cases the sharp transition responsible for the power loss takes place just before the last 50-60 e-foldings of inflation. We illustrate these general claims in the case of Fibre Inflation where we study the strength of this transition in terms of the attractor dynamics, finding that it induces a pivot from a blue to a redshifted power spectrum which can explain the apparent large scale power loss. We compute the effects of this pivot for example cases and demonstrate how magnitude and duration of this effect depend on model parameters.

Temperature of the inflaton and duration of inflation from Wilkinson microwave anisotropy probe data.

PubMed

Bhattacharya, Kaushik; Mohanty, Subhendra; Rangarajan, Raghavan

2006-03-31

If the initial state of the inflaton field is taken to have a thermal distribution instead of the conventional zero particle vacuum state then the curvature power spectrum gets modified by a temperature dependent factor such that the fluctuation spectrum of the microwave background radiation is enhanced at larger angles. We compare this modified cosmic microwave background spectrum with Wilkinson microwave anisotropy probe data to obtain an upper bound on the temperature of the inflaton at the time our current horizon crossed the horizon during inflation. We further conclude that there must be additional -foldings of inflation beyond what is needed to solve the horizon problem.

Spacetime Curvature and Higgs Stability after Inflation.

PubMed

Herranen, M; Markkanen, T; Nurmi, S; Rajantie, A

2015-12-11

We investigate the dynamics of the Higgs field at the end of inflation in the minimal scenario consisting of an inflaton field coupled to the standard model only through the nonminimal gravitational coupling ξ of the Higgs field. Such a coupling is required by renormalization of the standard model in curved space, and in the current scenario also by vacuum stability during high-scale inflation. We find that for ξ≳1, rapidly changing spacetime curvature at the end of inflation leads to significant production of Higgs particles, potentially triggering a transition to a negative-energy Planck scale vacuum state and causing an immediate collapse of the Universe.

The chaotic regime of D-term inflation

NASA Astrophysics Data System (ADS)

Buchmüller, W.; Domcke, V.; Schmitz, K.

2014-11-01

We consider D-term inflation for small couplings of the inflaton to matter fields. Standard hybrid inflation then ends at a critical value of the inflaton field that exceeds the Planck mass. During the subsequent waterfall transition the inflaton continues its slow-roll motion, whereas the waterfall field rapidly grows by quantum fluctuations. Beyond the decoherence time, the waterfall field becomes classical and approaches a time-dependent minimum, which is determined by the value of the inflaton field and the self-interaction of the waterfall field. During the final stage of inflation, the effective inflaton potential is essentially quadratic, which leads to the standard predictions of chaotic inflation. The model illustrates how the decay of a false vacuum of GUT-scale energy density can end in a period of `chaotic inflation'.

Main sequence models for massive zero-metal stars

NASA Technical Reports Server (NTRS)

Cary, N.

1974-01-01

Zero-age main-sequence models for stars of 20, 10, 5, and 2 solar masses with no heavy elements are constructed for three different possible primordial helium abundances: Y=0.00, Y=0.23, and Y=0.30. The latter two values of Y bracket the range of primordial helium abundances cited by Wagoner. With the exceptions of the two 20 solar mass models that contain helium, these models are found to be self-consistent in the sense that the formation of carbon through the triple-alpha process during premain sequence contraction is not sufficient to bring the CN cycle into competition with the proton-proton chain on the ZAMS. The zero-metal models of the present study have higher surface and central temperatures, higher central densities, smaller radii, and smaller convective cores than do the population I models with the same masses.

The interactive bending wrinkling behaviour of inflated beams

PubMed Central

Liu, Y. P.; Tan, H. F.; Wadee, M. K.

2016-01-01

A model is proposed based on a Fourier series method to analyse the interactive bending wrinkling behaviour of inflated beams. The whole wrinkling evolution is tracked and divided into three stages by identifying the bifurcations of the equilibrium path. The critical wrinkling and failure moments of the inflated beam can then be predicted. The global–local interactive buckling pattern is elucidated by the proposed theoretical model and also verified by non-contact experimental tests. The effects of geometric parameters, internal pressure and boundary conditions on the buckling of inflated beams are investigated finally. The results reveal that the interactive buckling characteristics of an inflated beam under bending are more sensitive to the dimensions of the structure and boundary conditions. We find that for beams which are simply supported at both ends or clamped and simply supported, boundary conditions may prevent the wrinkling formation. The results provide significant support for our understanding of the bending wrinkling behaviour of inflated beams. PMID:27713665

Is inflation from unwinding fluxes IIB?

NASA Astrophysics Data System (ADS)

Gautason, Fridrik Freyr; Schillo, Marjorie; Van Riet, Thomas

2017-03-01

In this paper we argue that the mechanism of unwinding inflation is naturally present in warped compactifications of type IIB string theory with local throats. The unwinding of flux is caused by its annihilation against branes. The resulting inflaton potential is linear with periodic modulations. We initiate an analysis of the inflationary dynamics and cosmological observables, which are highly constrained by moduli stabilization. For the simplified model of single-Kähler Calabi-Yau spaces we find that many, though not all of the consistency constraints can be satisfied. Particularly, in this simple model geometric constraints are in tension with obtaining the observed amplitude of the scalar power spectrum. However, we do find 60 efolds of inflation with a trans-Planckian field excursion which offers the hope that slightly more complicated models can lead to a fully consistent explicit construction of large field inflation of this kind.

Curvature perturbation and waterfall dynamics in hybrid inflation

NASA Astrophysics Data System (ADS)

Akbar Abolhasani, Ali; Firouzjahi, Hassan; Sasaki, Misao

2011-10-01

We investigate the parameter spaces of hybrid inflation model with special attention paid to the dynamics of waterfall field and curvature perturbations induced from its quantum fluctuations. Depending on the inflaton field value at the time of phase transition and the sharpness of the phase transition inflation can have multiple extended stages. We find that for models with mild phase transition the induced curvature perturbation from the waterfall field is too large to satisfy the COBE normalization. We investigate the model parameter space where the curvature perturbations from the waterfall quantum fluctuations vary between the results of standard hybrid inflation and the results obtained here.

Dynamic Deployment Simulations of Inflatable Space Structures

NASA Technical Reports Server (NTRS)

Wang, John T.

2005-01-01

The feasibility of using Control Volume (CV) method and the Arbitrary Lagrangian Eulerian (ALE) method in LSDYNA to simulate the dynamic deployment of inflatable space structures is investigated. The CV and ALE methods were used to predict the inflation deployments of three folded tube configurations. The CV method was found to be a simple and computationally efficient method that may be adequate for modeling slow inflation deployment sine the inertia of the inflation gas can be neglected. The ALE method was found to be very computationally intensive since it involves the solving of three conservative equations of fluid as well as dealing with complex fluid structure interactions.

Tobit analysis of vehicle accident rates on interstate highways.

PubMed

Anastasopoulos, Panagiotis Ch; Tarko, Andrew P; Mannering, Fred L

2008-03-01

There has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a continuous variable that is left-censored at zero. Using data from vehicle accidents on Indiana interstates, the estimation results show that many factors relating to pavement condition, roadway geometrics and traffic characteristics significantly affect vehicle accident rates.

[A simple model for describing pressure-volume curves in free balloon dilatation with reference the dynamics of inflation hydraulic aspects].

PubMed

Bloss, P; Werner, C

2000-06-01

We propose a simple model to describe pressure-time and pressure-volume curves for the free balloon (balloon in air) of balloon catheters, taking into account the dynamics of the inflation device. On the basis of our investigations of the flow rate-dependence of characteristic parameters of the pressure-time curves, the appropriateness of this simple model is demonstrated using a representative example. Basic considerations lead to the following assumptions: (1) the flow within the shaft of the catheter is laminar, and (ii) the volume decrease of the liquid used for inflation due to pressurization can be neglected if the liquid is carefully degassed prior to inflation, and if the total volume of the liquid in the system is less than 2 ml. Taking into account the dynamics of the inflation device used for pumping the liquid into the proximal end of the shaft during inflation, the inflation process can be subdivided into the following three phases: initial phase, filling phase and dilatation phase. For these three phases, the transformation of the time into the volume coordinates is given. On the basis of our model, the following parameters of the balloon catheter can be determined from a measured pressure-time curve: (1) the resistance to flow of the liquid through the shaft of the catheter and the resulting pressure drop across the shaft, (2) the residual volume and residual pressure of the balloon, and (3) the volume compliance of the balloon catheter with and without the inflation device.

Supergravity contributions to inflation in models with non-minimal coupling to gravity

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

Das, Kumar; Dutta, Koushik; Domcke, Valerie, E-mail: kumar.das@saha.ac.in, E-mail: valerie.domcke@apc.univ-paris7.fr, E-mail: koushik.dutta@saha.ac.in

2017-03-01

This paper provides a systematic study of supergravity contributions relevant for inflationary model building in Jordan frame supergravity. In this framework, canonical kinetic terms in the Jordan frame result in the separation of the Jordan frame scalar potential into a tree-level term and a supergravity contribution which is potentially dangerous for sustaining inflation. We show that if the vacuum energy necessary for driving inflation originates dominantly from the F-term of an auxiliary field (i.e. not the inflaton), the supergravity corrections to the Jordan frame scalar potential are generically suppressed. Moreover, these supergravity contributions identically vanish if the superpotential vanishes alongmore » the inflationary trajectory. On the other hand, if the F-term associated with the inflaton dominates the vacuum energy, the supergravity contributions are generically comparable to the globally supersymmetric contributions. In addition, the non-minimal coupling to gravity inherent to Jordan frame supergravity significantly impacts the inflationary model depending on the size and sign of this coupling. We discuss the phenomenology of some representative inflationary models, and point out the relation to the recently much discussed cosmological 'attractor' models.« less

Warm natural inflation

NASA Astrophysics Data System (ADS)

Mishra, Hiranmaya; Mohanty, Subhendra; Nautiyal, Akhilesh

2012-04-01

In warm inflation models there is the requirement of generating large dissipative couplings of the inflaton with radiation, while at the same time, not de-stabilising the flatness of the inflaton potential due to radiative corrections. One way to achieve this without fine tuning unrelated couplings is by supersymmetry. In this Letter we show that if the inflaton and other light fields are pseudo-Nambu-Goldstone bosons then the radiative corrections to the potential are suppressed and the thermal corrections are small as long as the temperature is below the symmetry breaking scale. In such models it is possible to fulfil the contrary requirements of an inflaton potential which is stable under radiative corrections and the generation of a large dissipative coupling of the inflaton field with other light fields. We construct a warm inflation model which gives the observed CMB-anisotropy amplitude and spectral index where the symmetry breaking is at the GUT scale.

What is the cause of confidence inflation in the Life Events Inventory (LEI) paradigm?

PubMed

Von Glahn, Nicholas R; Otani, Hajime; Migita, Mai; Langford, Sara J; Hillard, Erin E

2012-01-01

Briefly imagining, paraphrasing, or explaining an event causes people to increase their confidence that this event occurred during childhood-the imagination inflation effect. The mechanisms responsible for the effect were investigated with a new paradigm. In Experiment 1, event familiarity (defined as processing fluency) was varied by asking participants to rate each event once, three times, or five times. No inflation was found, indicating that familiarity does not account for the effect. In Experiment 2, richness of memory representation was manipulated by asking participants to generate zero, three, or six details. Confidence increased from the initial to the final rating in the three- and six-detail conditions, indicating that the effect is based on reality-monitoring errors. However, greater inflation in the three-detail condition than in the six-detail condition indicated that there is a boundary condition. These results were also consistent with an alternative hypothesis, the mental workload hypothesis.

Robustness of inflation to inhomogeneous initial conditions

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

Clough, Katy; Lim, Eugene A.; DiNunno, Brandon S.

We consider the effects of inhomogeneous initial conditions in both the scalar field profile and the extrinsic curvature on different inflationary models. In particular, we compare the robustness of small field inflation to that of large field inflation, using numerical simulations with Einstein gravity in 3+1 dimensions. We find that small field inflation can fail in the presence of subdominant gradient energies, suggesting that it is much less robust to inhomogeneities than large field inflation, which withstands dominant gradient energies. However, we also show that small field inflation can be successful even if some regions of spacetime start out inmore » the region of the potential that does not support inflation. In the large field case, we confirm previous results that inflation is robust if the inflaton occupies the inflationary part of the potential. Furthermore, we show that increasing initial scalar gradients will not form sufficiently massive inflation-ending black holes if the initial hypersurface is approximately flat. Finally, we consider the large field case with a varying extrinsic curvature K , such that some regions are initially collapsing. We find that this may again lead to local black holes, but overall the spacetime remains inflationary if the spacetime is open, which confirms previous theoretical studies.« less

Robustness of inflation to inhomogeneous initial conditions

NASA Astrophysics Data System (ADS)

Clough, Katy; Lim, Eugene A.; DiNunno, Brandon S.; Fischler, Willy; Flauger, Raphael; Paban, Sonia

2017-09-01

We consider the effects of inhomogeneous initial conditions in both the scalar field profile and the extrinsic curvature on different inflationary models. In particular, we compare the robustness of small field inflation to that of large field inflation, using numerical simulations with Einstein gravity in 3+1 dimensions. We find that small field inflation can fail in the presence of subdominant gradient energies, suggesting that it is much less robust to inhomogeneities than large field inflation, which withstands dominant gradient energies. However, we also show that small field inflation can be successful even if some regions of spacetime start out in the region of the potential that does not support inflation. In the large field case, we confirm previous results that inflation is robust if the inflaton occupies the inflationary part of the potential. Furthermore, we show that increasing initial scalar gradients will not form sufficiently massive inflation-ending black holes if the initial hypersurface is approximately flat. Finally, we consider the large field case with a varying extrinsic curvature K, such that some regions are initially collapsing. We find that this may again lead to local black holes, but overall the spacetime remains inflationary if the spacetime is open, which confirms previous theoretical studies.

Seeing Double with K2: Testing Re-inflation with Two Remarkably Similar Planets around Red Giant Branch Stars

NASA Astrophysics Data System (ADS)

Grunblatt, Samuel K.; Huber, Daniel; Gaidos, Eric; Lopez, Eric D.; Howard, Andrew W.; Isaacson, Howard T.; Sinukoff, Evan; Vanderburg, Andrew; Nofi, Larissa; Yu, Jie; North, Thomas S. H.; Chaplin, William; Foreman-Mackey, Daniel; Petigura, Erik; Ansdell, Megan; Weiss, Lauren; Fulton, Benjamin; Lin, Douglas N. C.

2017-12-01

Despite more than 20 years since the discovery of the first gas giant planet with an anomalously large radius, the mechanism for planet inflation remains unknown. Here, we report the discovery of K2-132b, an inflated gas giant planet found with the NASA K2 Mission, and a revised mass for another inflated planet, K2-97b. These planets orbit on ≈9 day orbits around host stars that recently evolved into red giants. We constrain the irradiation history of these planets using models constrained by asteroseismology and Keck/High Resolution Echelle Spectrometer spectroscopy and radial velocity measurements. We measure planet radii of 1.31 ± 0.11 R J and 1.30 ± 0.07 R J, respectively. These radii are typical for planets receiving the current irradiation, but not the former, zero age main-sequence irradiation of these planets. This suggests that the current sizes of these planets are directly correlated to their current irradiation. Our precise constraints of the masses and radii of the stars and planets in these systems allow us to constrain the planetary heating efficiency of both systems as 0.03{ % }-0.02 % +0.03 % . These results are consistent with a planet re-inflation scenario, but suggest that the efficiency of planet re-inflation may be lower than previously theorized. Finally, we discuss the agreement within 10% of the stellar masses and radii, and the planet masses, radii, and orbital periods of both systems, and speculate that this may be due to selection bias in searching for planets around evolved stars.

A study on industrial accident rate forecasting and program development of estimated zero accident time in Korea.

PubMed

Kim, Tae-gu; Kang, Young-sig; Lee, Hyung-won

2011-01-01

To begin a zero accident campaign for industry, the first thing is to estimate the industrial accident rate and the zero accident time systematically. This paper considers the social and technical change of the business environment after beginning the zero accident campaign through quantitative time series analysis methods. These methods include sum of squared errors (SSE), regression analysis method (RAM), exponential smoothing method (ESM), double exponential smoothing method (DESM), auto-regressive integrated moving average (ARIMA) model, and the proposed analytic function method (AFM). The program is developed to estimate the accident rate, zero accident time and achievement probability of an efficient industrial environment. In this paper, MFC (Microsoft Foundation Class) software of Visual Studio 2008 was used to develop a zero accident program. The results of this paper will provide major information for industrial accident prevention and be an important part of stimulating the zero accident campaign within all industrial environments.

Unidimensional factor models imply weaker partial correlations than zero-order correlations.

PubMed

van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J

2018-06-01

In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.

High dimensional linear regression models under long memory dependence and measurement error

NASA Astrophysics Data System (ADS)

Kaul, Abhishek

This dissertation consists of three chapters. The first chapter introduces the models under consideration and motivates problems of interest. A brief literature review is also provided in this chapter. The second chapter investigates the properties of Lasso under long range dependent model errors. Lasso is a computationally efficient approach to model selection and estimation, and its properties are well studied when the regression errors are independent and identically distributed. We study the case, where the regression errors form a long memory moving average process. We establish a finite sample oracle inequality for the Lasso solution. We then show the asymptotic sign consistency in this setup. These results are established in the high dimensional setup (p> n) where p can be increasing exponentially with n. Finally, we show the consistency, n½ --d-consistency of Lasso, along with the oracle property of adaptive Lasso, in the case where p is fixed. Here d is the memory parameter of the stationary error sequence. The performance of Lasso is also analysed in the present setup with a simulation study. The third chapter proposes and investigates the properties of a penalized quantile based estimator for measurement error models. Standard formulations of prediction problems in high dimension regression models assume the availability of fully observed covariates and sub-Gaussian and homogeneous model errors. This makes these methods inapplicable to measurement errors models where covariates are unobservable and observations are possibly non sub-Gaussian and heterogeneous. We propose weighted penalized corrected quantile estimators for the regression parameter vector in linear regression models with additive measurement errors, where unobservable covariates are nonrandom. The proposed estimators forgo the need for the above mentioned model assumptions. We study these estimators in both the fixed dimension and high dimensional sparse setups, in the latter setup, the

Rapid roll inflation with conformal coupling

NASA Astrophysics Data System (ADS)

Kofman, Lev; Mukohyama, Shinji

2008-02-01

Usual inflation is realized with a slow rolling scalar field minimally coupled to gravity. In contrast, we consider dynamics of a scalar with a flat effective potential, conformally coupled to gravity. Surprisingly, it contains an attractor inflationary solution with the rapidly rolling inflaton field. We discuss models with the conformal inflaton with a flat potential (including hybrid inflation). There is no generation of cosmological fluctuations from the conformally coupled inflaton. We consider realizations of modulated (inhomogeneous reheating) or curvaton cosmological fluctuations in these models. We also implement these unusual features for the popular string-theoretic warped inflationary scenario, based on the interacting D3-D¯3 branes. The original warped brane inflation suffers a large inflaton mass due to conformal coupling to 4-dimensional gravity. Instead of considering this as a problem and trying to cure it with extra engineering, we show that warped inflation with the conformally coupled, rapidly rolling inflaton is yet possible with N=37 efoldings, which requires low-energy scales 1 100 TeV of inflation. Coincidentally, the same warping numerology can be responsible for the hierarchy. It is shown that the scalars associated with angular isometries of the warped geometry of compact manifold (e.g. S3 of Klebanov-Strassler (KS) geometry) have solutions identical to conformally coupled modes and also cannot be responsible for cosmological fluctuations. We discuss other possibilities.

Modification of the Mantel-Haenszel and Logistic Regression DIF Procedures to Incorporate the SIBTEST Regression Correction

ERIC Educational Resources Information Center

DeMars, Christine E.

2009-01-01

The Mantel-Haenszel (MH) and logistic regression (LR) differential item functioning (DIF) procedures have inflated Type I error rates when there are large mean group differences, short tests, and large sample sizes.When there are large group differences in mean score, groups matched on the observed number-correct score differ on true score,…

Inflation in random Gaussian landscapes

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

Masoumi, Ali; Vilenkin, Alexander; Yamada, Masaki, E-mail: ali@cosmos.phy.tufts.edu, E-mail: vilenkin@cosmos.phy.tufts.edu, E-mail: Masaki.Yamada@tufts.edu

2017-05-01

We develop analytic and numerical techniques for studying the statistics of slow-roll inflation in random Gaussian landscapes. As an illustration of these techniques, we analyze small-field inflation in a one-dimensional landscape. We calculate the probability distributions for the maximal number of e-folds and for the spectral index of density fluctuations n {sub s} and its running α {sub s} . These distributions have a universal form, insensitive to the correlation function of the Gaussian ensemble. We outline possible extensions of our methods to a large number of fields and to models of large-field inflation. These methods do not suffer frommore » potential inconsistencies inherent in the Brownian motion technique, which has been used in most of the earlier treatments.« less

London equation for monodromy inflation

NASA Astrophysics Data System (ADS)

Kaloper, Nemanja; Lawrence, Albion

2017-03-01

We focus on the massive gauge theory formulation of axion monodromy inflation. We argue that a gauge symmetry hidden in these models is the key mechanism protecting inflation from dangerous field theory and quantum gravity corrections. The effective theory of large-field inflation is dual to a massive U (1 ) 4-form gauge theory, which is similar to a massive gauge theory description of superconductivity. The gauge theory explicitly realizes the old Julia-Toulouse proposal for a low-energy description of a gauge theory in a defect condensate. While we work mostly with the example of quadratic axion potential induced by flux monodromy, we discuss how other types of potentials can arise from the inclusion of gauge-invariant corrections to the theory.

Bispectrum from open inflation

NASA Astrophysics Data System (ADS)

Sugimura, Kazuyuki; Komatsu, Eiichiro

2013-11-01

We calculate the bispectrum of primordial curvature perturbations, ζ, generated during ``open inflation.'' Inflation occurs inside a bubble nucleated via quantum tunneling from the background false vacuum state. Our universe lives inside the bubble, which can be described as a Friedmann-Lemaȋtre-Robertson-Walker (FLRW) universe with negative spatial curvature, undergoing slow-roll inflation. We pay special attention to the issue of an initial state for quantum fluctuations. A ``vacuum state'' defined by a positive-frequency mode in de Sitter space charted by open coordinates is different from the Euclidean vacuum (which is equivalent to the so-called ``Bunch-Davies vacuum'' defined by a positive-frequency mode in de Sitter space charted by flat coordinates). Quantum tunneling (bubble nucleation) then modifies the initial state away from the original Euclidean vacuum. While most of the previous study on modifications of the initial quantum state introduces, by hand, an initial time at which the quantum state is modified as well as the form of the modification, an effective initial time naturally emerges and the form is fixed by quantum tunneling in open inflation models. Therefore, open inflation enables a self-consistent computation of the effect of a modified initial state on the bispectrum. We find a term which goes as langleζk1ζk2ζk3ranglepropto1/k12k34 in the so-called squeezed configurations, k3 << k1 ≈ k2, in agreement with the previous study on modifications of the initial state. The bispectrum in the exact folded limit, e.g., k1 = k2+k3, is also enhanced and remains finite. However, these terms are exponentially suppressed when the wavelength of ζ is smaller than the curvature radius of the universe. The leading-order bispectrum is equal to the usual one from single-field slow-roll inflation; the terms specific for open inflation arise only in the sub-leading order when the wavelength of ζ is smaller than the curvature radius.

The comparison of robust partial least squares regression with robust principal component regression on a real

NASA Astrophysics Data System (ADS)

Polat, Esra; Gunay, Suleyman

2013-10-01

One of the problems encountered in Multiple Linear Regression (MLR) is multicollinearity, which causes the overestimation of the regression parameters and increase of the variance of these parameters. Hence, in case of multicollinearity presents, biased estimation procedures such as classical Principal Component Regression (CPCR) and Partial Least Squares Regression (PLSR) are then performed. SIMPLS algorithm is the leading PLSR algorithm because of its speed, efficiency and results are easier to interpret. However, both of the CPCR and SIMPLS yield very unreliable results when the data set contains outlying observations. Therefore, Hubert and Vanden Branden (2003) have been presented a robust PCR (RPCR) method and a robust PLSR (RPLSR) method called RSIMPLS. In RPCR, firstly, a robust Principal Component Analysis (PCA) method for high-dimensional data on the independent variables is applied, then, the dependent variables are regressed on the scores using a robust regression method. RSIMPLS has been constructed from a robust covariance matrix for high-dimensional data and robust linear regression. The purpose of this study is to show the usage of RPCR and RSIMPLS methods on an econometric data set, hence, making a comparison of two methods on an inflation model of Turkey. The considered methods have been compared in terms of predictive ability and goodness of fit by using a robust Root Mean Squared Error of Cross-validation (R-RMSECV), a robust R2 value and Robust Component Selection (RCS) statistic.

Model Checking Techniques for Assessing Functional Form Specifications in Censored Linear Regression Models.

PubMed

León, Larry F; Cai, Tianxi

2012-04-01

In this paper we develop model checking techniques for assessing functional form specifications of covariates in censored linear regression models. These procedures are based on a censored data analog to taking cumulative sums of "robust" residuals over the space of the covariate under investigation. These cumulative sums are formed by integrating certain Kaplan-Meier estimators and may be viewed as "robust" censored data analogs to the processes considered by Lin, Wei & Ying (2002). The null distributions of these stochastic processes can be approximated by the distributions of certain zero-mean Gaussian processes whose realizations can be generated by computer simulation. Each observed process can then be graphically compared with a few realizations from the Gaussian process. We also develop formal test statistics for numerical comparison. Such comparisons enable one to assess objectively whether an apparent trend seen in a residual plot reects model misspecification or natural variation. We illustrate the methods with a well known dataset. In addition, we examine the finite sample performance of the proposed test statistics in simulation experiments. In our simulation experiments, the proposed test statistics have good power of detecting misspecification while at the same time controlling the size of the test.

[From clinical judgment to linear regression model.

PubMed

Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

2013-01-01

When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-12-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

USGS Publications Warehouse

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-01-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

G-warm inflation

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

Herrera, Ramón, E-mail: ramon.herrera@pucv.cl

A warm inflationary universe in the context of Galileon model or G-model is studied. Under a general formalism we study the inflationary dynamics and the cosmological perturbations considering a coupling of the form G (φ, X )= g (φ) X . As a concrete example, we consider an exponential potential together with the cases in which the dissipation and Galilean coefficients are constants. Also, we study the weak regime given by the condition R <1+3 gH φ-dot , and the strong regime in which 1< R +3 gH φ-dot . Additionally, we obtain constraints on the parameters during the evolutionmore » of G-warm inflation, assuming the condition for warm inflation in which the temperature T > H , the conditions or the weak and strong regimes, together with the consistency relation r = r ( n {sub s} ) from Planck data.« less

Distinguishing between extra natural inflation and natural inflation after BICEP2

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

Kohri, Kazunori; Lim, C.S.; Lin, Chia-Min, E-mail: kohri@post.kek.jp, E-mail: lim@lab.twcu.ac.jp, E-mail: lin@chuo-u.ac.jp

2014-08-01

In this paper, we carefully calculated the tensor-to-scalar ratio, the running spectral index, and the running of running spectrum for (extra) natural inflation in order to compare with recent BICEP2 data, PLANCK satellite data and future 21 cm data. We discovered that the prediction for running spectral index and the running of running spectrum in natural inflation is different from that in the case of extra natural inflation. Near future observation for the running spectral index can only provide marginal accuracy which may not allow us distinguishing between extra natural inflation from natural inflation clearly unless the experimental accuracy canmore » be further improved.« less

Dynamic Characterization of an Inflatable Concentrator for Solar Thermal Propulsion

NASA Technical Reports Server (NTRS)

Leigh, Larry; Hamidzadeh, Hamid; Tinker, Michael L.; Rodriguez, Pedro I. (Technical Monitor)

2001-01-01

An inflatable structural system that is a technology demonstrator for solar thermal propulsion and other applications is characterized for structural dynamic behavior both experimentally and computationally. The inflatable structure is a pressurized assembly developed for use in orbit to support a Fresnel lens or inflatable lenticular element for focusing sunlight into a solar thermal rocket engine. When the engine temperature reaches a pre-set level, the propellant is injected into the engine, absorbs heat from an exchanger, and is expanded through the nozzle to produce thrust. The inflatable structure is a passively adaptive system in that a regulator and relief valve are utilized to maintain pressure within design limits during the full range of orbital conditions. Modeling and test activities are complicated by the fact that the polyimide film material used for construction of the inflatable is nonlinear, with modulus varying as a function of frequency, temperature, and level of excitation. Modal vibration testing and finite element modeling are described in detail in this paper. The test database is used for validation and modification of the model. This work is highly significant because of the current interest in inflatable structures for space application, and because of the difficulty in accurately modeling such systems.

Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

PubMed

Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

2017-02-06

Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

Towards an explicit model of large field inflation

NASA Astrophysics Data System (ADS)

Dorronsoro, Juan Diaz; Schillo, Marjorie

2018-05-01

The unwinding inflation mechanism is studied in a type IIB flux compactification where all moduli are stabilized using flux, non-perturbative effects, and the leading α' corrections of the large volume scenario. We consider the backreaction on the geometry due to the presence of anti-D3 branes as well as the backreaction of inflation on the Kähler moduli, and compute the resulting corrections to the slow-roll potential. By taking large flux numbers, we are able to find inflationary epochs where backreaction effects are under control, the inflaton traverses a super-Planckian field range, and the resulting amplitude of scalar perturbations is consistent with observation.

The Other Inflation

ERIC Educational Resources Information Center

Aristides

1976-01-01

The other inflation is grade inflation, the label affixed to the indisputable rise in the grade-point averages of undergraduates at public and private, elite and community colleges and universities across the country. The effects of grade inflation upon academic performance were assessed. (Author/RK)

First observational tests of eternal inflation.

PubMed

Feeney, Stephen M; Johnson, Matthew C; Mortlock, Daniel J; Peiris, Hiranya V

2011-08-12

The eternal inflation scenario predicts that our observable Universe resides inside a single bubble embedded in a vast inflating multiverse. We present the first observational tests of eternal inflation, performing a search for cosmological signatures of collisions with other bubble universes in cosmic microwave background data from the WMAP satellite. We conclude that the WMAP 7-year data do not warrant augmenting the cold dark matter model with a cosmological constant with bubble collisions, constraining the average number of detectable bubble collisions on the full sky N(s) < 1.6 at 68% C.L. Data from the Planck satellite can be used to more definitively test the bubble-collision hypothesis.

Inflatable Vessel and Method

NASA Technical Reports Server (NTRS)

Raboin, Jasen L. (Inventor); Valle, Gerard D. (Inventor); Edeen, Gregg A. (Inventor); delaFuente, Horacio M. (Inventor); Schneider, William C. (Inventor); Spexarth, Gary R. (Inventor); Pandya, Shalini Gupta (Inventor); Johnson, Christopher J. (Inventor)

2003-01-01

An inflatable module comprising a structural core and an inflatable shell, wherein the inflatable shell is sealingly attached to the structural core. In its launch or pre-deployed configuration, the wall thickness of the inflatable shell is collapsed by vacuum. Also in this configuration, the inflatable shell is collapsed and efficiently folded around the structural core. Upon deployment, the wall thickness of the inflatable shell is inflated; whereby the inflatable shell itself, is thereby inflated around the structural core, defining therein a large enclosed volume. A plurality of removable shelves are arranged interior to the structural core in the launch configuration. The structural core also includes at least one longeron that, in conjunction with the shelves, primarily constitute the rigid, strong, and lightweight load-bearing structure of the module during launch. The removable shelves are detachable from their arrangement in the launch configuration so that, when the module is in its deployed configuration and launch loads no longer exist, the shelves can be rearranged to provide a module interior arrangement suitable for human habitation and work. In the preferred embodiment, to provide efficiency in structural load paths and attachments, the shape of the inflatable shell is a cylinder with semi-toroidal ends.

Baryon asymmetry and gravitational waves from pseudoscalar inflation

NASA Astrophysics Data System (ADS)

Jiménez, Daniel; Kamada, Kohei; Schmitz, Kai; Xu, Xun-Jie

2017-12-01

In models of inflation driven by an axion-like pseudoscalar field, the inflaton, a, may couple to the standard model hypercharge via a Chern-Simons-type interaction, Script L ⊃ a/(4Λ) Ftilde F. This coupling results in explosive gauge field production during inflation, especially at its last stage, which has interesting phenomenological consequences: For one thing, the primordial hypermagnetic field is maximally helical. It is thus capable of sourcing the generation of nonzero baryon number, via the standard model chiral anomaly, around the time of electroweak symmetry breaking. For another thing, the gauge field production during inflation feeds back into the primordial tensor power spectrum, leaving an imprint in the stochastic background of gravitational waves (GWs). In this paper, we focus on the correlation between these two phenomena. Working in the approximation of instant reheating, we (1) update the investigation of baryogenesis via hypermagnetic fields from pseudoscalar inflation and (2) examine the corresponding implications for the GW spectrum. We find that successful baryogenesis requires a suppression scale Λ of around Λ ~ 3 × 1017 GeV, which corresponds to a relatively weakly coupled axion. The gauge field production at the end of inflation is then typically accompanied by a peak in the GW spectrum at frequencies in the MHz range or above. The detection of such a peak is out of reach of present-day technology; but in the future, it may serve as a smoking-gun signal for baryogenesis from pseudoscalar inflation. Conversely, models that do yield an observable GW signal suffer from the overproduction of baryon number, unless the reheating temperature is lower than the electroweak scale.

Deployment Simulation of Ultra-Lightweight Inflatable Structures

NASA Technical Reports Server (NTRS)

Wang, John T.; Johnson, Arthur R.

2002-01-01

Dynamic deployment analyses of folded inflatable tubes are conducted to investigate modeling issues related to the deployment of solar sail booms. The analyses are necessary because ground tests include gravity effects and may poorly represent deployment in space. A control volume approach, available in the LS-DYNA nonlinear dynamic finite element code, and the ideal gas law are used to simulate the dynamic inflation deployment process. Three deployment issues are investigated for a tube packaged in a Z-fold configuration. The issues are the effect of the rate of inflation, the effect of residual air, and the effect of gravity. The results of the deployment analyses reveal that the time and amount of inflation gas required to achieve a full deployment are related to these issues.

Permutation on hybrid natural inflation

NASA Astrophysics Data System (ADS)

Carone, Christopher D.; Erlich, Joshua; Ramos, Raymundo; Sher, Marc

2014-09-01

We analyze a model of hybrid natural inflation based on the smallest non-Abelian discrete group S3. Leading invariant terms in the scalar potential have an accidental global symmetry that is spontaneously broken, providing a pseudo-Goldstone boson that is identified as the inflaton. The S3 symmetry restricts both the form of the inflaton potential and the couplings of the inflaton field to the waterfall fields responsible for the end of inflation. We identify viable points in the model parameter space. Although the power in tensor modes is small in most of the parameter space of the model, we identify parameter choices that yield potentially observable values of r without super-Planckian initial values of the inflaton field.

The paradoxical zero reflection at zero energy

NASA Astrophysics Data System (ADS)