Picture 1 of 1
Stock photo
Picture 1 of 1
Stock photo
Chapman and Hall/Crc Texts in Statistical Science Ser.: Bayesian Data Analysis by Andrew Gelman (2003, Hardcover)
S
Select Discounts Shop (4699)
90.8% positive feedback
Price:
US $45.05
ApproximatelyAU $69.07
+ $36.87 postage
Returns:
30-day returns. Buyer pays for return postage. If you use an eBay postage label, it will be deducted from your refund amount.
Condition:
For sale is Bayesian Data Analysis Andrew Gelman! Over the years we have learned how to provide our customers with reliably fast shipping and low prices on books and textbooks. Choose priority shipping upon checkout for fastest shipping speeds. We ship fast, we are based in the USA for efficient delivery to nearly all homes and colleges across the USA, and we ship to nearly ALL INTERNATIONAL locations too!
- Buy It NowBayesian Data Analysis Andrew Gelman
Oops! Looks like we're having trouble connecting to our server.
Refresh your browser window to try again.
About this product
Product Identifiers
PublisherCRC Press LLC
ISBN-10158488388X
ISBN-139781584883883
eBay Product ID (ePID)2309770467
Product Key Features
Number of Pages690 Pages
LanguageEnglish
Publication NameBayesian Data Analysis
Publication Year2003
SubjectProbability & Statistics / General, Probability & Statistics / Bayesian Analysis
TypeTextbook
Subject AreaMathematics
AuthorAndrew Gelman
SeriesChapman and Hall/Crc Texts in Statistical Science Ser.
FormatHardcover
Dimensions
Item Height1.6 in
Item Weight38.5 Oz
Item Length9.3 in
Item Width6.4 in
Additional Product Features
Edition Number2
Intended AudienceCollege Audience
LCCN2003-051474
Dewey Edition21
Series Volume Number106
IllustratedYes
Dewey Decimal519.542
Edition DescriptionRevised edition,New Edition
Table Of ContentFUNDAMENTALS 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
SynopsisIncorporating 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 NumberQA279.5.B386 2003
