Bayesian data analysis
By: Andrew Gelman, ... [et al.]
Contributors: Gelman, Andrew.
Edition: 1st CRC reprint
Series: Chapman & Hall texts in statistical science series
Publisher: Chapman & Hall/CRC
Published: 2000
Place of publication: Boca Raton, FL
Language: eng
Number of pages: 526
Subjects: Bayesian statistical decision theory; Mathematical statistics
Description: "Bayesian Data Analysis is a comprehensive treatment of the statistical analysis of data from a Bayesian perspective. Modern computational tools are emphasized, and inferences are typically obtained using computer simulations.".

"The principles of Bayesian analysis are described with an emphasis on practical rather than theoretical issues, and illustrated using actual data. A variety of models are considered, including linear regression, hierarchical (random effects) models, robust models, generalized linear models and mixture models.".

"Two important and unique features of this text are thorough discussions of the methods for checking Bayesian models and the role of the design of data collection in influencing Bayesian statistical analysis." "Issues of data collection, model formulation, computation, model checking and sensitivity analysis are all considered. The student or practising statistician will find that there is guidance on all aspects of Bayesian data analysis."--BOOK JACKET.
Notes: Reprint of the reprinted ed. with corrections 1998.

Includes bibliographical references (p. [489]-512) and indexes.