Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical

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Item specifics

Condition
Good: A book that has been read but is in good condition. Very minimal damage to the cover including ...
Book Title
Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts
ISBN
9781584883883
Subject Area
Mathematics
Publication Name
Bayesian Data Analysis
Publisher
CRC Press LLC
Item Length
9.3 in
Subject
Probability & Statistics / General, Probability & Statistics / Bayesian Analysis
Publication Year
2003
Series
Chapman and Hall/Crc Texts in Statistical Science Ser.
Type
Textbook
Format
Hardcover
Language
English
Item Height
1.6 in
Author
Andrew Gelman
Item Weight
38.5 Oz
Item Width
6.4 in
Number of Pages
690 Pages
Category

About this product

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
158488388X
ISBN-13
9781584883883
eBay Product ID (ePID)
2309770467

Product Key Features

Number of Pages
690 Pages
Language
English
Publication Name
Bayesian Data Analysis
Publication Year
2003
Subject
Probability & Statistics / General, Probability & Statistics / Bayesian Analysis
Type
Textbook
Subject Area
Mathematics
Author
Andrew Gelman
Series
Chapman and Hall/Crc Texts in Statistical Science Ser.
Format
Hardcover

Dimensions

Item Height
1.6 in
Item Weight
38.5 Oz
Item Length
9.3 in
Item Width
6.4 in

Additional Product Features

Edition Number
2
Intended Audience
College Audience
LCCN
2003-051474
Dewey Edition
21
Series Volume Number
106
Illustrated
Yes
Dewey Decimal
519.542
Edition Description
Revised edition,New Edition
Table Of Content
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 Improvement Modeling Accounting for Data Collection Connections and Controversies General Advice ADVANCED COMPUTATION Overview of Computation Posterior Simulation Approximations Based on Posterior Modes Topics in Computation REGRESSION MODELS Introduction to Regression Models Hierarchical Linear Models Generalized Linear Models Models for Robust Inference and Sensitivity Analysis Analysis of Variance SPECIFIC MODELS AND PROBLEMS Mixture Models Multivariate Models Nonlinear Models Models for Missing Data Decision Analysis APPENDICES A: Standard Probability Distributions B: Outline of Proofs of Asymptotic Theorems C: Example of Computation in R and Bugs References
Synopsis
Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include: Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collection Bayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.
LC Classification Number
QA279.5.B386 2003

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