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Contributions To Bayesian Statistical Inference Microform
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Author :Lehana Thabane Publisher :National Library of Canada = Bibliothèque nationale du Canada ISBN 13 :9780612311336 Total Pages :432 pages Book Rating :4.3/5 (113 download)
Book Synopsis Contributions to Bayesian Statistical Inference [microform] by : Lehana Thabane
Download or read book Contributions to Bayesian Statistical Inference [microform] written by Lehana Thabane and published by National Library of Canada = Bibliothèque nationale du Canada. This book was released on 1998 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Behrens-Fisher (BF) problem deals with comparison of means of two normal population with different variance parameters. We have provided an alternative Bayesian approach to the multivariate BF problem using the Kullback-Leibler divergence measure. We have also derived the solution of the BF problem for class of elliptically symmetric distributions. Here, we have shown that the original solution obtained under the normality assumption remains optimal under this class.
Book Synopsis Contributions to Bayesian Statistical Inference by :
Download or read book Contributions to Bayesian Statistical Inference written by and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Some Contributions to Bayesian Nonparametric Statistical Inference by : Albert Yee-Lap Lo
Download or read book Some Contributions to Bayesian Nonparametric Statistical Inference written by Albert Yee-Lap Lo and published by . This book was released on 1978 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Some Contributions to Bayesian Nonparametric Statistical Inference by : Albert Yee-Lap
Download or read book Some Contributions to Bayesian Nonparametric Statistical Inference written by Albert Yee-Lap and published by . This book was released on 1978 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Contributions to Bayesian Statistical Analysis by : Milovan Krnjajić
Download or read book Contributions to Bayesian Statistical Analysis written by Milovan Krnjajić and published by . This book was released on 2005 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Some Contributions to Approximate Inference in Bayesian Statistics by : Xiaole Zhang
Download or read book Some Contributions to Approximate Inference in Bayesian Statistics written by Xiaole Zhang and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bayesian Inference on Complicated Data by : Niansheng Tang
Download or read book Bayesian Inference on Complicated Data written by Niansheng Tang and published by BoD – Books on Demand. This book was released on 2020-07-15 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to great applications in various fields, such as social science, biomedicine, genomics, and signal processing, and the improvement of computing ability, Bayesian inference has made substantial developments for analyzing complicated data. This book introduces key ideas of Bayesian sampling methods, Bayesian estimation, and selection of the prior. It is structured around topics on the impact of the choice of the prior on Bayesian statistics, some advances on Bayesian sampling methods, and Bayesian inference for complicated data including breast cancer data, cloud-based healthcare data, gene network data, and longitudinal data. This volume is designed for statisticians, engineers, doctors, and machine learning researchers.
Book Synopsis Frontiers of Statistical Decision Making and Bayesian Analysis by : Ming-Hui Chen
Download or read book Frontiers of Statistical Decision Making and Bayesian Analysis written by Ming-Hui Chen and published by Springer Science & Business Media. This book was released on 2010-07-24 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.
Book Synopsis New Ways in Statistical Methodology by : Henry Rouanet
Download or read book New Ways in Statistical Methodology written by Henry Rouanet and published by Peter Lang Publishing. This book was released on 1998 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents work developed within the Mathematics and Psychology Group of the French National Center for Scientific Research. New trends in statistical methodology are presented, along with an analysis of researchers' attitudes toward statistical inference, and concrete proposals for improving statistical practice. Discussion encompasses combinatorial inference, fiducial Bayesian inference, Bayesian inference for categorized data, and geometric data. Of interest to researchers, statisticians, and statistics users in behavioral and social sciences. Rouanet is director of research at the French National Center for Scientific Research at the University Rene Descartes. Annotation copyrighted by Book News, Inc., Portland, OR.
Book Synopsis Proceedings of the Section on Bayesian Statistical Science by : American Statistical Association. Section on Bayesian Statistical Science
Download or read book Proceedings of the Section on Bayesian Statistical Science written by American Statistical Association. Section on Bayesian Statistical Science and published by . This book was released on 1998 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 956 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advancements in Bayesian Methods and Implementations by :
Download or read book Advancements in Bayesian Methods and Implementations written by and published by Academic Press. This book was released on 2022-10-06 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in Bayesian Methods and Implementation, Volume 47 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Fisher Information, Cramer-Rao and Bayesian Paradigm, Compound beta binomial distribution functions, MCMC for GLMMS, Signal Processing and Bayesian, Mathematical theory of Bayesian statistics where all models are wrong, Machine Learning and Bayesian, Non-parametric Bayes, Bayesian testing, and Data Analysis with humans, Variational inference or Functional horseshoe, Generalized Bayes. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Advancements in Bayesian Methods and Implementation
Book Synopsis A Demonstration of Bayesian Statistical Inference in Education Research by : Megan N. Shoji
Download or read book A Demonstration of Bayesian Statistical Inference in Education Research written by Megan N. Shoji and published by . This book was released on 2012 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bayesian Analysis in Statistics and Econometrics by : Prem K. Goel
Download or read book Bayesian Analysis in Statistics and Econometrics written by Prem K. Goel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is based on the invited and the contributed presentations given at the Indo-U.S. Workshop on Bayesian Analysis in Statistics and Econometrics (BASE), Dec. 19-23, 1988, held at the Hotel Taj Residency, Bangalore, India. The workshop was jointly sponsored by The Ohio State University, The Indian Statistical Institute, The Indian Econometrics So ciety, U.S. National Science Foundation and the NSF-NBER Seminar on Bayesian Inference in Econometrics. Profs. Morrie DeGroot, Prem Goel, and Arnold Zellner were the program organizers. Unfortunately, Morrie became seriously ill just before the workshop was to start and could not participate in the workshop. Almost a year later, Morrie passed away after fighting valiantly with the illness. Not to find Morrie among ourselves was a shock for most of us. He was a continuous source of inspiration and ideas. Even while Morrie was fighting for his life, we had a lot of discussions about the contents of this volume and the Bangalore Workshop. He even talked about organizing a Second Indo-U.S. workshop some time in the near future. We are dedicating this volume to the memory of Prof. Morris H. DeGroot. We have taken a conscious decision not to include any biography of Morrie in this volume. An excellent biography of Morrie has appeared in Statistical Science [(1991), vol. 6, 1-14], and we could not have done a better job than that.
Book Synopsis Bayesian Inference for Partially Identified Models by : Paul Gustafson
Download or read book Bayesian Inference for Partially Identified Models written by Paul Gustafson and published by CRC Press. This book was released on 2015-04-01 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially identified contexts. Drawing on his many years of research in this area, the author presents a thorough overview of the statistical theory, properties, and applications of PIMs. The book first describes how reparameterization can assist in computing posterior quantities and providing insight into the properties of Bayesian estimators. It next compares partial identification and model misspecification, discussing which is the lesser of the two evils. The author then works through PIM examples in depth, examining the ramifications of partial identification in terms of how inferences change and the extent to which they sharpen as more data accumulate. He also explains how to characterize the value of information obtained from data in a partially identified context and explores some recent applications of PIMs. In the final chapter, the author shares his thoughts on the past and present state of research on partial identification. This book helps readers understand how to use Bayesian methods for analyzing PIMs. Readers will recognize under what circumstances a posterior distribution on a target parameter will be usefully narrow versus uselessly wide.
Download or read book Data in Doubt written by John Denis Hey and published by . This book was released on 1985 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Francisco J. Samaniego Publisher :Springer Science & Business Media ISBN 13 :1441959416 Total Pages :235 pages Book Rating :4.4/5 (419 download)
Book Synopsis A Comparison of the Bayesian and Frequentist Approaches to Estimation by : Francisco J. Samaniego
Download or read book A Comparison of the Bayesian and Frequentist Approaches to Estimation written by Francisco J. Samaniego and published by Springer Science & Business Media. This book was released on 2010-06-14 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main theme of this monograph is “comparative statistical inference. ” While the topics covered have been carefully selected (they are, for example, restricted to pr- lems of statistical estimation), my aim is to provide ideas and examples which will assist a statistician, or a statistical practitioner, in comparing the performance one can expect from using either Bayesian or classical (aka, frequentist) solutions in - timation problems. Before investing the hours it will take to read this monograph, one might well want to know what sets it apart from other treatises on comparative inference. The two books that are closest to the present work are the well-known tomes by Barnett (1999) and Cox (2006). These books do indeed consider the c- ceptual and methodological differences between Bayesian and frequentist methods. What is largely absent from them, however, are answers to the question: “which - proach should one use in a given problem?” It is this latter issue that this monograph is intended to investigate. There are many books on Bayesian inference, including, for example, the widely used texts by Carlin and Louis (2008) and Gelman, Carlin, Stern and Rubin (2004). These books differ from the present work in that they begin with the premise that a Bayesian treatment is called for and then provide guidance on how a Bayesian an- ysis should be executed. Similarly, there are many books written from a classical perspective.
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