Bayesian Methods for Statistical Analysis (Borek Puza)

 
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Bayesian Methods for Statistical Analysis (Borek Puza)

A book on statistical techniques for analyzing a wide range of data is called Bayesian approaches for statistical analysis.

The book is divided into 12 chapters that cover a wide range of 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 begins with fundamental concepts and moves on to more advanced ideas.

Numerous tasks are included in the book, all of which have working solutions that include the entire computer code. With three hours of lectures and one tutorial each week for 13 weeks, it is appropriate for independent study or a semester-long course.

Ebook Details

Author(s)
About the Authors
In the Research School of Finance, Actuarial Studies, and Statistics, Dr. Borek Puza teaches statistics. He holds a BSc in Mathematics and a Ph.D., Master's, and Graduate Diploma in Statistics.
Publisher
Published
Published Date / Year
(September 15, 2017)
License(s)
Creative Commons
Hardcover
698 pages
eBook Format
PDF (697 pages, 6.4 MB)
Language
English
ISBN-10
1921934255
ISBN-13
978-1921934254

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