Bayesian methods for statistical analysis

Bayesian methods for statistical analysis

Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical m...

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Bibliographic Details
Other Authors: Puza, Borek, author (author)
Format: eBook
Language:Inglés
Published: Australia : ANU Press 2015
2015.
Edition:1st ed
Subjects:
Bayesian statistical decision theory.
statistics
mathematics
bayesian inference
probability
Algorithm
Confidence interval
Histogram
Monte Carlo method
Posterior probability
Sampling (statistics)
WinBUGS
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009439556806719
Table of Contents:
  • Intro
  • Abstract
  • Acknowledgements
  • Preface
  • Overview
  • 1. Bayesian Basics Part 1
  • 2. Bayesian Basics Part 2
  • 3. Bayesian Basics Part 3
  • 4. Computational Tools
  • 5. Monte Carlo Basics
  • 6. MCMC Methods Part 1
  • 7. MCMC Methods Part 2
  • 8. Inference via WinBUGS
  • 9. Bayesian Finite Population Theory
  • 10. Normal Finite Population Models
  • 11. Transformations and Other Topics
  • 12. Biased Sampling and Nonresponse
  • Appendix A: Additional Exercises
  • Appendix B: Distributions and Notation
  • Appendix C: Abbreviations and Acronyms
  • Bibliography.

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