Empirical Bayes Methods With Applications

Author : J.S. Maritz
Publisher : CRC Press
Page : 210 pages
File Size : 44,6 Mb
Release : 2018-01-18
Category : Mathematics
ISBN : 9781351088565

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Empirical Bayes Methods with Applications by J.S. Maritz Pdf

The second edition of Empirical Bayes Methods details are provided of the derivation and the performance of empirical Bayes rules for a variety of special models. Attention is given to the problem of assessing the goodness of an empirical Bayes estimator for a given set of prior data. A chapter is devoted to a discussion of alternatives to the empirical Bayes approach and there is also a chapter giving details of several actual applications of empirical Bayes method.

Author : J. S. Maritz
Publisher : Unknown
Page : 176 pages
File Size : 51,5 Mb
Release : 1970
Category : Mathematics
ISBN : STANFORD:36105041078887

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Empirical Bayes Methods by J. S. Maritz Pdf

Author : J.S. Maritz
Publisher : CRC Press
Page : 296 pages
File Size : 52,7 Mb
Release : 2018-01-18
Category : Mathematics
ISBN : 9781351080118

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Empirical Bayes Methods with Applications by J.S. Maritz Pdf

The second edition of Empirical Bayes Methods details are provided of the derivation and the performance of empirical Bayes rules for a variety of special models. Attention is given to the problem of assessing the goodness of an empirical Bayes estimator for a given set of prior data. A chapter is devoted to a discussion of alternatives to the empirical Bayes approach and there is also a chapter giving details of several actual applications of empirical Bayes method.

Author : Bradley Efron
Publisher : Cambridge University Press
Page : 128 pages
File Size : 51,6 Mb
Release : 2012-11-29
Category : Mathematics
ISBN : 9781139492133

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Large-Scale Inference by Bradley Efron Pdf

We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.

Author : Bradley P. Carlin
Publisher : Unknown
Page : 399 pages
File Size : 52,7 Mb
Release : 1996
Category : Analysis of variance
ISBN : OCLC:1147746521

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Bayes and Empirical Bayes Methods for Data Analysis by Bradley P. Carlin Pdf

Author : J. S. Maritz,T. Lwin
Publisher : Routledge
Page : 288 pages
File Size : 50,6 Mb
Release : 2018-03-05
Category : Business & Economics
ISBN : 9781351140621

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Empirical Bayes Methods by J. S. Maritz,T. Lwin Pdf

Originally published in 1970; with a second edition in 1989. Empirical Bayes methods use some of the apparatus of the pure Bayes approach, but an actual prior distribution is assumed to generate the data sequence. It can be estimated thus producing empirical Bayes estimates or decision rules. In this second edition, details are provided of the derivation and the performance of empirical Bayes rules for a variety of special models. Attention is given to the problem of assessing the goodness of an empirical Bayes estimator for a given set of prior data. Chapters also focus on alternatives to the empirical Bayes approach and actual applications of empirical Bayes methods.

Author : David R. Bickel
Publisher : CRC Press
Page : 141 pages
File Size : 49,9 Mb
Release : 2019-09-24
Category : Mathematics
ISBN : 9781000706918

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Genomics Data Analysis by David R. Bickel Pdf

Statisticians have met the need to test hundreds or thousands of genomics hypotheses simultaneously with novel empirical Bayes methods that combine advantages of traditional Bayesian and frequentist statistics. Techniques for estimating the local false discovery rate assign probabilities of differential gene expression, genetic association, etc. without requiring subjective prior distributions. This book brings these methods to scientists while keeping the mathematics at an elementary level. Readers will learn the fundamental concepts behind local false discovery rates, preparing them to analyze their own genomics data and to critically evaluate published genomics research. Key Features: * dice games and exercises, including one using interactive software, for teaching the concepts in the classroom * examples focusing on gene expression and on genetic association data and briefly covering metabolomics data and proteomics data * gradual introduction to the mathematical equations needed * how to choose between different methods of multiple hypothesis testing * how to convert the output of genomics hypothesis testing software to estimates of local false discovery rates * guidance through the minefield of current criticisms of p values * material on non-Bayesian prior p values and posterior p values not previously published

Author : Vladimir Savchuk,Chris P. Tsokos
Publisher : Springer Science & Business Media
Page : 327 pages
File Size : 53,8 Mb
Release : 2011-09-01
Category : Mathematics
ISBN : 9789491216145

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Bayesian Theory and Methods with Applications by Vladimir Savchuk,Chris P. Tsokos Pdf

Bayesian methods are growing more and more popular, finding new practical applications in the fields of health sciences, engineering, environmental sciences, business and economics and social sciences, among others. This book explores the use of Bayesian analysis in the statistical estimation of the unknown phenomenon of interest. The contents demonstrate that where such methods are applicable, they offer the best possible estimate of the unknown. Beyond presenting Bayesian theory and methods of analysis, the text is illustrated with a variety of applications to real world problems.

Author : Satyanshu K. Upadhyay,Umesh Singh,Dipak K. Dey,Appaia Loganathan
Publisher : CRC Press
Page : 674 pages
File Size : 47,5 Mb
Release : 2015-05-21
Category : Mathematics
ISBN : 9781482235128

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Current Trends in Bayesian Methodology with Applications by Satyanshu K. Upadhyay,Umesh Singh,Dipak K. Dey,Appaia Loganathan Pdf

Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics. Each chapter is self-contained and focuses on a Bayesian methodology. It gives an overview of the area, presents theoretical insights, and emphasizes applications through motivating examples. This book reflects the diversity of Bayesian analysis, from novel Bayesian methodology, such as nonignorable response and factor analysis, to state-of-the-art applications in economics, astrophysics, biomedicine, oceanography, and other areas. It guides readers in using Bayesian techniques for a range of statistical analyses.

Author : Herbert Robbins
Publisher : Unknown
Page : 24 pages
File Size : 47,6 Mb
Release : 1955
Category : Bayesian statistical decision theory
ISBN : UOM:39015095244375

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An Empirical Bayes Approach to Statistics by Herbert Robbins Pdf

Author : Bradley P. Carlin,Thomas A. Louis
Publisher : CRC Press
Page : 552 pages
File Size : 43,6 Mb
Release : 2008-06-30
Category : Mathematics
ISBN : 1584886986

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Bayesian Methods for Data Analysis, Third Edition by Bradley P. Carlin,Thomas A. Louis Pdf

Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the foundations and applications of Bayesian analysis. Along with a complete reorganization of the material, this edition concentrates more on hierarchical Bayesian modeling as implemented via Markov chain Monte Carlo (MCMC) methods and related data analytic techniques. New to the Third Edition New data examples, corresponding R and WinBUGS code, and homework problems Explicit descriptions and illustrations of hierarchical modeling—now commonplace in Bayesian data analysis A new chapter on Bayesian design that emphasizes Bayesian clinical trials A completely revised and expanded section on ranking and histogram estimation A new case study on infectious disease modeling and the 1918 flu epidemic A solutions manual for qualifying instructors that contains solutions, computer code, and associated output for every homework problem—available both electronically and in print Ideal for Anyone Performing Statistical Analyses Focusing on applications from biostatistics, epidemiology, and medicine, this text builds on the popularity of its predecessors by making it suitable for even more practitioners and students.

Author : S. James Press
Publisher : Unknown
Page : 37 pages
File Size : 42,7 Mb
Release : 1965
Category : Logistics
ISBN : LCCN:70220564

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Statistical Estimation by the Empirical Bayes Method: Some Extensions and Logistical Applications by S. James Press Pdf

This report contains a presentation of the empirical Bayes procedure for improving existing methods of estimating statistical decision parameters which occur in such logistical problems as reliability, maintenance, and supply. It consists essentially of estimating a parameter by using an approximate Bayes estimator that does not depend on any previous information, other than earlier observations. The author presents estimators for the univariate and multivariate exponential family of distributions, for distributions with nuisance parameters, and for the distribution of a family of random variables (Poisson process). (Author).

Author : Chris Tsokos
Publisher : Elsevier
Page : 566 pages
File Size : 50,9 Mb
Release : 2012-12-02
Category : Technology & Engineering
ISBN : 9780323145855

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The Theory and Applications of Reliability With Emphasis on Bayesian and Nonparametric Methods by Chris Tsokos Pdf

The Theory and Applications of Reliability: With Emphasis on Bayesian and Nonparametric Methods, Volume I covers the proceedings of the conference on ""The Theory and Applications of Reliability with Emphasis on Bayesian and Nonparametric Methods."" The conference is organized so as to have technical presentations, a clinical session, and round table discussions. This volume is a 29-chapter text that specifically deals with the theoretical aspects of reliability estimation. Considerable chapters on the technical sessions are devoted to initial findings on the theory and applications of reliability estimation, with special emphasis on Bayesian and nonparametric methods. A Bayesian analysis implies the use of suitable prior information in association with Bayes theorem while the nonparametric approach analyzes the reliability components and systems under the assumption of a time-to-failure distribution with a wide defining property rather than a specific parametric class of probability distributions. The clinical session chapters discuss the actual problems encountered in reliability estimation. The remaining chapters deal with the status of the subject areas and the empirical Bayes developments. These chapters also present various probabilistic and statistic methods for reliability estimation. Theoreticians and reliability engineers will find this book invaluable.

Author : Bradley P. Carlin,Thomas A. Louis
Publisher : Chapman and Hall/CRC
Page : 440 pages
File Size : 42,6 Mb
Release : 2000-06-22
Category : Mathematics
ISBN : 1584881704

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Bayes and Empirical Bayes Methods for Data Analysis, Second Edition by Bradley P. Carlin,Thomas A. Louis Pdf

In recent years, Bayes and empirical Bayes (EB) methods have continued to increase in popularity and impact. Building on the first edition of their popular text, Carlin and Louis introduce these methods, demonstrate their usefulness in challenging applied settings, and show how they can be implemented using modern Markov chain Monte Carlo (MCMC) methods. Their presentation is accessible to those new to Bayes and empirical Bayes methods, while providing in-depth coverage valuable to seasoned practitioners. With its broad appeal as a text for those in biomedical science, education, social science, agriculture, and engineering, this second edition offers a relatively gentle and comprehensive introduction for students and practitioners already familiar with more traditional frequentist statistical methods. Focusing on practical tools for data analysis, the book shows how properly structured Bayes and EB procedures typically have good frequentist and Bayesian performance, both in theory and in practice.

Author : Sylvia Frühwirth-Schnatter,Angela Bitto,Gregor Kastner,Alexandra Posekany
Publisher : Springer
Page : 167 pages
File Size : 41,9 Mb
Release : 2015-05-19
Category : Mathematics
ISBN : 9783319162386

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Bayesian Statistics from Methods to Models and Applications by Sylvia Frühwirth-Schnatter,Angela Bitto,Gregor Kastner,Alexandra Posekany Pdf

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.