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Author Puza, Borek. Author.

Title Bayesian Methods for Statistical Analysis.

Imprint ANU Press 2015.

Copies

Location Call No. OPAC Message Status
 Axe JSTOR Open Ebooks  Electronic Book    ---  Available
Description 1 online resource
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
data file rda
Summary Bayesian methods for statistical analysisˇis 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 models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. 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.
Language English.
Bibliography Includes bibliographical references.
Contents 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.
Subject Bayesian statistical decision theory.
Mathematics.
Probability & statistics.
Bayesian inference.
Bayesian statistical decision theory. (OCoLC)fst00829019
Indexed Term statistics.
mathematics.
bayesian inference.
probability.
Genre/Form Electronic books.
Other Form: Print version: Puza, Borek. Bayesian methods for statistical analysis. Australia : Australian National University, ©2015 xvii, 679 pages 9781921934254
ISBN 9781921934254
1921934255
1921934263 (electronic bk.)
9781921934261 (electronic bk.)
Standard No. 10.26530/OAPEN_611011 doi
AU@ 000060582381
CHNEW 000974810
CHVBK 503252840
GBVCP 1008666637
GBVCP 865795657
GBVCP 869962183

 
    
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