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Bayesian Methods for Statistical Analysis.

By: Material type: TextTextPublisher: Canberra : ANU Press, 2015Copyright date: ©2015Edition: 1st edDescription: 1 online resource (697 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781921934261
Subject(s): Genre/Form: Additional physical formats: Print version:: Bayesian Methods for Statistical AnalysisDDC classification:
  • 519.54200000000003
LOC classification:
  • QA279.5.P893 2015
Online resources:
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.
Summary: Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of lectures and one tutorial per week for 13 weeks.
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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.

Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of lectures and one tutorial per week for 13 weeks.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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