Empirical Bayes Methods with Applications

Empirical Bayes Methods with Applications PDF

Author: J.S. Maritz

Publisher: Chapman and Hall/CRC

Published: 1989-06

Total Pages: 304

ISBN-13:

DOWNLOAD EBOOK →

Since the publication of the first edition of "Empirical Bayes methods" in 1970, there have been many contributions to the theory known as the empirical Bayes approach. This book collects and presents practical examples of the application of empirical Bayes ideas and techniques.

Empirical Bayes Methods with Applications

Empirical Bayes Methods with Applications PDF

Author: J.S. Maritz

Publisher: CRC Press

Published: 2018-01-18

Total Pages: 210

ISBN-13: 1351088564

DOWNLOAD EBOOK →

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.

Large-Scale Inference

Large-Scale Inference PDF

Author: Bradley Efron

Publisher: Cambridge University Press

Published: 2012-11-29

Total Pages:

ISBN-13: 1139492136

DOWNLOAD EBOOK →

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.

Bayesian Methods for Data Analysis, Third Edition

Bayesian Methods for Data Analysis, Third Edition PDF

Author: Bradley P. Carlin

Publisher: CRC Press

Published: 2008-06-30

Total Pages: 552

ISBN-13: 9781584886983

DOWNLOAD EBOOK →

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.

The Analysis of Gene Expression Data

The Analysis of Gene Expression Data PDF

Author: Giovanni Parmigiani

Publisher: Springer Science & Business Media

Published: 2006-04-11

Total Pages: 511

ISBN-13: 0387216790

DOWNLOAD EBOOK →

This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.

Empirical Bayes and Likelihood Inference

Empirical Bayes and Likelihood Inference PDF

Author: S.E. Ahmed

Publisher: Springer Science & Business Media

Published: 2001

Total Pages: 260

ISBN-13: 9780387950181

DOWNLOAD EBOOK →

Bayesian and such approaches to inference have a number of points of close contact, especially from an asymptotic point of view. Both emphasize the construction of interval estimates of unknown parameters. In this volume, researchers present recent work on several aspects of Bayesian, likelihood and empirical Bayes methods, presented at a workshop held in Montreal, Canada. The goal of the workshop was to explore the linkages among the methods, and to suggest new directions for research in the theory of inference.

Genomics Data Analysis

Genomics Data Analysis PDF

Author: David R. Bickel

Publisher: CRC Press

Published: 2019-09-24

Total Pages: 141

ISBN-13: 1000706915

DOWNLOAD EBOOK →

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

Data Gathering, Analysis and Protection of Privacy Through Randomized Response Techniques: Qualitative and Quantitative Human Traits

Data Gathering, Analysis and Protection of Privacy Through Randomized Response Techniques: Qualitative and Quantitative Human Traits PDF

Author:

Publisher: Elsevier

Published: 2016-04-20

Total Pages: 545

ISBN-13: 0444635718

DOWNLOAD EBOOK →

Data Gathering, Analysis and Protection of Privacy through Randomized Response Techniques: Qualitative and Quantitative Human Traits tackles how to gather and analyze data relating to stigmatizing human traits. S.L. Warner invented RRT and published it in JASA, 1965. In the 50 years since, the subject has grown tremendously, with continued growth. This book comprehensively consolidates the literature to commemorate the inception of RR. Brings together all relevant aspects of randomized response and indirect questioning Tackles how to gather and analyze data relating to stigmatizing human traits Gives an encyclopedic coverage of the topic Covers recent developments and extrapolates to future trends