Bayesian Analysis Of Linear Models
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Bayesian Analysis Of Linear Models
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Author : Broemeling
language : en
Publisher: CRC Press
Release Date : 1984-12-06
Bayesian Analysis Of Linear Models written by Broemeling and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984-12-06 with Mathematics categories.
This book presents the basic theory of linear models from a Bayesian viewpoint. It is unique in that time series models such as autoregressive moving average processes are treated as linear models in the same way the general linear model is examined.
Bayesian Analysis Of Linear Models
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Author : Lyle D. Broemeling
language : en
Publisher:
Release Date : 1985
Bayesian Analysis Of Linear Models written by Lyle D. Broemeling and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.
Bayesian Analysis Of Linear Models
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Author : Kenneth George Williams
language : en
Publisher:
Release Date : 1976
Bayesian Analysis Of Linear Models written by Kenneth George Williams and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with Analysis of variance categories.
Bayesian Analysis In Statistics And Econometrics
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Author : Donald A. Berry
language : en
Publisher: John Wiley & Sons
Release Date : 1996
Bayesian Analysis In Statistics And Econometrics written by Donald A. Berry and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Business & Economics categories.
This book is a definitive work that captures the current state of knowledge of Bayesian Analysis in Statistics and Econometrics and attempts to move it forward. It covers such topics as foundations, forecasting inferential matters, regression, computation and applications.
Bayesian Inference
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Author : Silvelyn Zwanzig
language : en
Publisher: CRC Press
Release Date : 2024-07-23
Bayesian Inference written by Silvelyn Zwanzig and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-23 with Mathematics categories.
Bayesian Inference: Theory, Methods, Computations provides a comprehensive coverage of the fundamentals of Bayesian inference from all important perspectives, namely theory, methods and computations. All theoretical results are presented as formal theorems, corollaries, lemmas etc., furnished with detailed proofs. The theoretical ideas are explained in simple and easily comprehensible forms, supplemented with several examples. A clear reasoning on the validity, usefulness, and pragmatic approach of the Bayesian methods is provided. A large number of examples and exercises, and solutions to all exercises, are provided to help students understand the concepts through ample practice. The book is primarily aimed at first or second semester master students, where parts of the book can also be used at Ph.D. level or by research community at large. The emphasis is on exact cases. However, to gain further insight into the core concepts, an entire chapter is dedicated to computer intensive techniques. Selected chapters and sections of the book can be used for a one-semester course on Bayesian statistics. Key Features: Explains basic ideas of Bayesian statistical inference in an easily comprehensible form Illustrates main ideas through sketches and plots Contains large number of examples and exercises Provides solutions to all exercises Includes R codes Silvelyn Zwanzig is a Professor for Mathematical Statistics at Uppsala University. She studied Mathematics at the Humboldt University of Berlin. Before coming to Sweden, she was Assistant Professor at the University of Hamburg in Germany. She received her Ph.D. in Mathematics at the Academy of Sciences of the GDR. She has taught Statistics to undergraduate and graduate students since 1991. Her research interests include theoretical statistics and computer-intensive methods. Rauf Ahmad is Associate Professor at the Department of Statistics, Uppsala University. He did his Ph.D. at the University of Göttingen, Germany. Before joining Uppsala University, he worked at the Division of Mathematical Statistics, Department of Mathematics, Linköping University, and at Biometry Division, Swedish University of Agricultural Sciences, Uppsala. He has taught Statistics to undergraduate and graduate students since 1995. His research interests include high-dimensional inference, mathematical statistics, and U-statistics.
Bayesian Analysis Of Time Series
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Author : Lyle D. Broemeling
language : en
Publisher: CRC Press
Release Date : 2019-04-16
Bayesian Analysis Of Time Series written by Lyle D. Broemeling and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-16 with Mathematics categories.
In many branches of science relevant observations are taken sequentially over time. Bayesian Analysis of Time Series discusses how to use models that explain the probabilistic characteristics of these time series and then utilizes the Bayesian approach to make inferences about their parameters. This is done by taking the prior information and via Bayes theorem implementing Bayesian inferences of estimation, testing hypotheses, and prediction. The methods are demonstrated using both R and WinBUGS. The R package is primarily used to generate observations from a given time series model, while the WinBUGS packages allows one to perform a posterior analysis that provides a way to determine the characteristic of the posterior distribution of the unknown parameters. Features Presents a comprehensive introduction to the Bayesian analysis of time series. Gives many examples over a wide variety of fields including biology, agriculture, business, economics, sociology, and astronomy. Contains numerous exercises at the end of each chapter many of which use R and WinBUGS. Can be used in graduate courses in statistics and biostatistics, but is also appropriate for researchers, practitioners and consulting statisticians. About the author Lyle D. Broemeling, Ph.D., is Director of Broemeling and Associates Inc., and is a consulting biostatistician. He has been involved with academic health science centers for about 20 years and has taught and been a consultant at the University of Texas Medical Branch in Galveston, The University of Texas MD Anderson Cancer Center and the University of Texas School of Public Health. His main interest is in developing Bayesian methods for use in medical and biological problems and in authoring textbooks in statistics. His previous books for Chapman & Hall/CRC include Bayesian Biostatistics and Diagnostic Medicine, and Bayesian Methods for Agreement.
Bayesian Statistics From Methods To Models And Applications
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Author : Sylvia Frühwirth-Schnatter
language : en
Publisher: Springer
Release Date : 2015-05-19
Bayesian Statistics From Methods To Models And Applications written by Sylvia Frühwirth-Schnatter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-19 with Mathematics categories.
The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to the 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Université Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session with 30 contributions. Selected contributions have been drawn from the conference for this book. All contributions in this volume are peer-reviewed and share original research in Bayesian computation, application, and theory.
Generalized Linear Models
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Author : Dipak K. Dey
language : en
Publisher: CRC Press
Release Date : 2000-05-25
Generalized Linear Models written by Dipak K. Dey and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-25 with Mathematics categories.
This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers
Bayesian Analysis Of Gaussian Mixed Linear Models Using Gibbs Sampling With Applications In Animal Breeding
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Author : Cunshan Wang
language : en
Publisher:
Release Date : 1993
Bayesian Analysis Of Gaussian Mixed Linear Models Using Gibbs Sampling With Applications In Animal Breeding written by Cunshan Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.
The Oxford Handbook Of Applied Bayesian Analysis
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Author : Anthony O' Hagan
language : en
Publisher: OUP Oxford
Release Date : 2010-03-18
The Oxford Handbook Of Applied Bayesian Analysis written by Anthony O' Hagan and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-18 with Mathematics categories.
Bayesian analysis has developed rapidly in applications in the last two decades and research in Bayesian methods remains dynamic and fast-growing. Dramatic advances in modelling concepts and computational technologies now enable routine application of Bayesian analysis using increasingly realistic stochastic models, and this drives the adoption of Bayesian approaches in many areas of science, technology, commerce, and industry. This Handbook explores contemporary Bayesian analysis across a variety of application areas. Chapters written by leading exponents of applied Bayesian analysis showcase the scientific ease and natural application of Bayesian modelling, and present solutions to real, engaging, societally important and demanding problems. The chapters are grouped into five general areas: Biomedical & Health Sciences; Industry, Economics & Finance; Environment & Ecology; Policy, Political & Social Sciences; and Natural & Engineering Sciences, and Appendix material in each touches on key concepts, models, and techniques of the chapter that are also of broader pedagogic and applied interest.