Bayesian Methods for Repeated Measures, Broemeling
Автор: Islam, M. Ataharul Название: Analysis of repeated measures data ISBN: 9811037930 ISBN-13(EAN): 9789811037931 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- Linear Models.- Univariate Exponential Family of Distributions.- Generalized Linear Model.- Covariate Dependent Markov Models.- Model for Bivariate Binary Data.- Model for Bivariate Geometric Model.- Model for Bivariate Count Data.- Models for Bivariate Exponential and Weibull Data.- Quasi -Likelihood Methods.- Generalized Estimating Equations.- A Generalized Multivariate Model.- Multistate and Multistage Models.- Analysing Data Using R and SAS.
Автор: Raghavarao Damaraju Название: Repeated Measurements and Cross-Over Designs ISBN: 111870925X ISBN-13(EAN): 9781118709252 Издательство: Wiley Рейтинг: Цена: 17733.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An introduction to state-of-the-art experimental design approaches to better understand and interpret repeated measurement data in cross-over designs.
Автор: Chen Ming-Hui, Shao Qi-Man, Ibrahim Joseph G. Название: Monte Carlo Methods in Bayesian Computation ISBN: 0387989358 ISBN-13(EAN): 9780387989358 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines advanced Bayesian computational methods. It presents methods for sampling from posterior distributions and discusses how to compute posterior quantities of interest using Markov chain Monte Carlo (MCMC) samples. This book examines each of these issues in detail and heavily focuses on computing various posterior quantities of interest from a given MCMC sample. Several topics are addressed, including techniques for MCMC sampling, Monte Carlo methods for estimation of posterior quantities, improving simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, highest posterior density interval calculations, computation of posterior modes, and posterior computations for proportional hazards models and Dirichlet process models. The authors also discuss computions involving model comparisons, including both nested and non-nested models, marginal likelihood methods, ratios of normalizing constants, Bayes factors, the Savage-Dickey density ratio, Stochastic Search Variable Selection, Bayesian Model Averaging, the reverse jump algorithm, and model adequacy using predictive and latent residual approaches.The book presents an equal mixture of theory and applications involving real data. The book is intended as a graduate textbook or a reference book for a one semester course at the advanced masters or Ph.D. level. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners.Ming-Hui Chen is Associate Professor of Mathematical Sciences at Worcester Polytechnic Institute, Qu-Man Shao is Assistant Professor of Mathematics at the University of Oregon. Joseph G. Ibrahim is Associate Professor of Biostatistics at the Harvard School of Public Health and Dana-Farber Cancer Institute.
Автор: Wakefield Название: Bayesian and Frequentist Regression Methods ISBN: 1441909249 ISBN-13(EAN): 9781441909244 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis.
Автор: J. P. Verma Название: Repeated Measures Design for Empirical Researchers ISBN: 1119052718 ISBN-13(EAN): 9781119052715 Издательство: Wiley Рейтинг: Цена: 17574.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Discusses how to conceptualize research problems as well as identify appropriate repeated measures designs for research purposes. In this book, examples have been chosen from multiple domains, including psychology, the social sciences, management, and sports science, to aid readers in understanding both the associated theories and methodologies.
Автор: Charles S. Davis Название: Statistical Methods for the Analysis of Repeated Measurements ISBN: 1441929762 ISBN-13(EAN): 9781441929761 Издательство: Springer Рейтинг: Цена: 13969.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: I have endeavored to provide a comprehensive introduction to a wide - riety of statistical methods for the analysis of repeated measurements. I envision this book primarily as a textbook, because the notes on which it is based have been used in a semester-length graduate course I have taught since1991.Thiscourseisprimarilytakenbygraduatestudentsinbiostat- tics and statistics, although students and faculty from other departments have audited the course. I also anticipate that the book will be a useful r- erence for practicing statisticians. This assessment is based on the positive responses I have received to numerous short courses I have taught on this topic to academic and industry groups. Althoughmyintentistoprovideareasonablycomprehensiveoverviewof methodsfortheanalysisofrepeatedmeasurements, Idonotviewthisbook as a de?nitive "state of the art" compendium of research in this area. Some general approaches are extremely active areas of current research, and it is not feasible, given the goals of this book, to include a comprehensive summary and list of references. Instead, my focus is primarily on methods that are implemented in standard statistical software packages. As a result, thelevelofdetailonsometopicsislessthaninotherbooks, andsomemore recent methods of analysis are not included. One particular example is the topic of nonlinear mixed models for the analysis of repeated measurements (Davidian and Giltinan, 1995; Vonesh and Chinchilli, 1996). With respect to some of the more recent methods of analysis, I do attempt to mention some of the areas of current research.
Описание: Sampling from the posterior distribution and computing posterior quanti- ties of interest using Markov chain Monte Carlo (MCMC) samples are two major challenges involved in advanced Bayesian computation. This book examines each of these issues in detail and focuses heavily on comput- ing various posterior quantities of interest from a given MCMC sample. Several topics are addressed, including techniques for MCMC sampling, Monte Carlo (MC) methods for estimation of posterior summaries, improv- ing simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, Highest Poste- rior Density (HPD) interval calculations, computation of posterior modes, and posterior computations for proportional hazards models and Dirichlet process models. Also extensive discussion is given for computations in- volving model comparisons, including both nested and nonnested models. Marginal likelihood methods, ratios of normalizing constants, Bayes fac- tors, the Savage-Dickey density ratio, Stochastic Search Variable Selection (SSVS), Bayesian Model Averaging (BMA), the reverse jump algorithm, and model adequacy using predictive and latent residual approaches are also discussed. The book presents an equal mixture of theory and real applications.
Автор: Thomas Hamelryck; Kanti Mardia; Jesper Ferkinghoff Название: Bayesian Methods in Structural Bioinformatics ISBN: 3642439888 ISBN-13(EAN): 9783642439889 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This edited volume is a high-profile overview of the current state of play in statistical methods applied to structural bioinformatics. With almost 100 pages of introductory material, it covers topics including protein structure prediction and simulation.
Автор: John Skilling Название: Maximum Entropy and Bayesian Methods ISBN: 0792302249 ISBN-13(EAN): 9780792302247 Издательство: Springer Рейтинг: Цена: 41647.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Wolfgang von der Linden; Volker Dose; Rainer Fisch Название: Maximum Entropy and Bayesian Methods Garching, Germany 1998 ISBN: 9401059829 ISBN-13(EAN): 9789401059824 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proceedings of the 18th International Workshop on Maximum Entropy and Bayesian Methods of Statistical Analysis
Автор: Daniel Sorensen; Daniel Gianola Название: Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics ISBN: 1441929975 ISBN-13(EAN): 9781441929976 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits.
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