The Resource Bayes and empirical Bayes methods for data analysis, Bradley P. Carlin and Thomas A. Louis

Bayes and empirical Bayes methods for data analysis, Bradley P. Carlin and Thomas A. Louis

Label
Bayes and empirical Bayes methods for data analysis
Title
Bayes and empirical Bayes methods for data analysis
Statement of responsibility
Bradley P. Carlin and Thomas A. Louis
Creator
Contributor
Subject
Language
eng
Summary
"As a result of recent advances in computing and the consequent ability to evaluate complex models, Bayes and empirical Bayes (EB) methods have increased in popularity for data analysis. Bayes and Empirical Bayes Methods for Data Analysis introduces these methods, demonstrates their usefulness in challenging applied settings and shows how they can be implemented using modern Markov chain Monte Carlo (MCMC) computational methods. The book avoids philosophical nit-picking, and instead shows how properly structured Bayes and EB procedures typically have good frequentist and Bayesian performance both in theory and practice." "The book provides a guide to the commercial and noncommercial software available for performing Bayes and EB analyses, including the electronic availability of each via e-mail and the World Wide Web. Practicing statisticians and biostatisticians analyzing complex data sets from industry, agriculture, biomedical science and public health will value this book. It will also be of great interest to statistical consultants and researchers, as well as Master's and Ph. D. students in the above areas."--Jacket
Member of
Action
committed to retain for EAST
Cataloging source
EUN
http://library.link/vocab/creatorName
Carlin, Bradley P
Illustrations
illustrations
Index
index present
LC call number
QA279.5
LC item number
.C37 1996
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1944-
http://library.link/vocab/relatedWorkOrContributorName
Louis, Thomas A.
http://library.link/vocab/subjectName
  • Bayesian statistical decision theory
  • Analysis of variance
  • Electronic data processing
  • Information storage and retrieval systems
  • Punched card systems
  • Analyse des données
  • Méthodes statistiques
  • Analysis of variance
  • Bayesian statistical decision theory
  • Electronic data processing
  • Information storage and retrieval systems
  • Punched card systems
  • Methode van Bayes
  • Data-analyse
  • Inferencia estatistica
  • Analise de dados
  • Bayes-Verfahren
  • Datenanalyse
Label
Bayes and empirical Bayes methods for data analysis, Bradley P. Carlin and Thomas A. Louis
Instantiates
Publication
Bibliography note
Includes bibliographical references (p.[363]-386) and indexes
Carrier category
volume
Carrier category code
nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Some basic Bayesian models
  • A Gaussian/Gaussian (normal/normal) model
  • A beta/binomial model
  • The Bayes approach
  • Prior distributions
  • Elicited priors
  • Conjugate priors
  • Noninformative priors
  • Other prior construction methods
  • Bayesian inference
  • Approaches for statistical inference
  • Point estimation
  • Interval estimation
  • Hypothesis testing and Bayes factors
  • Example: Consumer preference data
  • Model assessment
  • Diagnostic measures
  • Model averaging
  • Nonparametric methods
  • The empirical Bayes approach
  • Nonparametric EB (NPEB) point estimation
  • Motivating vignettes
  • Compound sampling models
  • Simple NPEB (Robbins' method)
  • Example: Accident data
  • Parametric EB (PEB) point estimation
  • Gaussian/Gaussian models
  • Beta/binomial model
  • EB performance of the PEB
  • Stein estimation
  • Computation via the EM algorithm
  • EM for PEB
  • Personal probability
  • Computing the observed information
  • EM for NPEB
  • Speeding convergence and generalizations
  • Interval estimation
  • Morris' approach
  • Marginal posterior approach
  • Bias correction approach
  • Generalization to regression structures
  • Performance of Bayes procedures
  • Bayesian processing
  • Missing data
  • Univariate stretching with a two-point prior
  • Multivariate Gaussian model
  • Frequentist performance: Point estimates
  • Gaussian/Gaussian model
  • Beta/binomial model
  • Generalization
  • Bioassay
  • Attenuation adjustment
  • Defining the approaches
  • The Bayes-frequentist controversy
Dimensions
23 cm.
Edition
1st ed.
Extent
xvi, 399 pages
Isbn
9780412056116
Media category
unmediated
Media MARC source
rdamedia
Media type code
n
Other physical details
illustrations
System control number
  • (OCoLC)35110631
  • (OCoLC)ocm35110631
Label
Bayes and empirical Bayes methods for data analysis, Bradley P. Carlin and Thomas A. Louis
Publication
Bibliography note
Includes bibliographical references (p.[363]-386) and indexes
Carrier category
volume
Carrier category code
nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Some basic Bayesian models
  • A Gaussian/Gaussian (normal/normal) model
  • A beta/binomial model
  • The Bayes approach
  • Prior distributions
  • Elicited priors
  • Conjugate priors
  • Noninformative priors
  • Other prior construction methods
  • Bayesian inference
  • Approaches for statistical inference
  • Point estimation
  • Interval estimation
  • Hypothesis testing and Bayes factors
  • Example: Consumer preference data
  • Model assessment
  • Diagnostic measures
  • Model averaging
  • Nonparametric methods
  • The empirical Bayes approach
  • Nonparametric EB (NPEB) point estimation
  • Motivating vignettes
  • Compound sampling models
  • Simple NPEB (Robbins' method)
  • Example: Accident data
  • Parametric EB (PEB) point estimation
  • Gaussian/Gaussian models
  • Beta/binomial model
  • EB performance of the PEB
  • Stein estimation
  • Computation via the EM algorithm
  • EM for PEB
  • Personal probability
  • Computing the observed information
  • EM for NPEB
  • Speeding convergence and generalizations
  • Interval estimation
  • Morris' approach
  • Marginal posterior approach
  • Bias correction approach
  • Generalization to regression structures
  • Performance of Bayes procedures
  • Bayesian processing
  • Missing data
  • Univariate stretching with a two-point prior
  • Multivariate Gaussian model
  • Frequentist performance: Point estimates
  • Gaussian/Gaussian model
  • Beta/binomial model
  • Generalization
  • Bioassay
  • Attenuation adjustment
  • Defining the approaches
  • The Bayes-frequentist controversy
Dimensions
23 cm.
Edition
1st ed.
Extent
xvi, 399 pages
Isbn
9780412056116
Media category
unmediated
Media MARC source
rdamedia
Media type code
n
Other physical details
illustrations
System control number
  • (OCoLC)35110631
  • (OCoLC)ocm35110631

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