Bayesian Data Analysis / Edition 4

Bayesian Data Analysis / Edition 4

3.0 2
by Andrew Gelman, John B. Carlin, Hal S. Stern, Donald B. Rubin
     
 

ISBN-10: 0412039915

ISBN-13: 9780412039911

Pub. Date: 01/28/1995

Publisher: Taylor & Francis

Bayesian Data Analysis describes how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Using examples largely from the authors' own experiences, the book focuses on modern computational tools and obtains inferences using computer simulations. Its unique features include thorough discussions of the methods for checking

Overview

Bayesian Data Analysis describes how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Using examples largely from the authors' own experiences, the book focuses on modern computational tools and obtains inferences using computer simulations. Its unique features include thorough discussions of the methods for checking Bayesian models and the role of the design of data collection in influencing Bayesian statistical analysis.
Bayesian Data Analysis offers the practicing statistician singular guidance on all aspects of the subject.

Product Details

ISBN-13:
9780412039911
Publisher:
Taylor & Francis
Publication date:
01/28/1995
Series:
Chapman & Hall/CRC Texts in Statistical Science Series
Edition description:
Older Edition
Pages:
552
Product dimensions:
6.33(w) x 9.39(h) x 1.07(d)
Age Range:
18 Years

Related Subjects

Table of Contents

Fundamentals of Bayesian Inference Background Single-Parameter Models Introduction to Multiparameter Models Large-Sample Inference and Connections to Standard Statistical Methods Fundamentals of Bayesian Data Analysis Hierarchical Models Model Checking and Sensitivity Analysis Study Design in Bayesian Analysis Introduction to Regression Models Advanced Computation Approximations Based on Posterior Modes Posterior Simulation and Integration Markov Chain Simulation Specific Models Models of Robust Inference and Sensitivity Analysis Hierarchical Linear Models Generalized Linear Models Multivariate Models Mixture Models Models for Missing Data Concluding Advice Appendixes Standard Probability Distributions Outline of Proofs of Asymptotic Theorems

Customer Reviews

Average Review:

Write a Review

and post it to your social network

     

Most Helpful Customer Reviews

See all customer reviews >