Applied Bayesian Statistics With R and OpenBUGS Examples / by Mary Kathryn Cowles.

This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been used by students of different levels and disciplines, including advanced undergraduates studying Mathematics and Statistics and students in graduate programs  in Statistics, Biostatis...

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Bibliographic Details
Main Author: Cowles, Mary Kathryn (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2013.
Edition:1st ed. 2013.
Series:Springer Texts in Statistics, 98
Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • What is Bayesian statistics?
  • Review of probability
  • Introduction to one-parameter models
  • Inference for a population proportion
  • Special considerations in Bayesian inference
  • Other one-parameter models and their conjugate priors
  • More realism please: Introduction to multiparameter models
  • Fitting more complex Bayesian models: Markov chain Monte Carlo
  • Hierarchical models, and more on convergence assessment
  • Regression and hierarchical regression models
  • Model Comparison, Model Checking, and Hypothesis Testing
  • References
  • Index.