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This textbook by Peter D. Hoff provides a compact, self-contained introduction to Bayesian statistical methods. It covers both theoretical foundations and practical applications, aimed at users with a basic knowledge of probability calculus. The material supports an in-depth understanding of Bayesian statistical methods and the associated computational techniques.
Description
The book gives a clear explanation of probability, exchangeability, and Bayes’ rule as the basis for Bayesian statistical methods. Numerous examples with R code are directly applicable, so that readers can carry out the data analyses themselves. In addition, Monte Carlo and Markov chain Monte Carlo methods are developed within concrete data analysis examples, emphasizing the motivation and applicability of these statistical methods.
Product specifications
- Author: Peter D. Hoff
- Series: Springer Texts in Statistics
- Publisher: Springer-Verlag New York Inc.
- Publication date: 2009-06-15
- Number of pages: 271
- ISBN: 9780387922997
- Theme: Probability and statistics
- BISAC: MATHEMATICS / Probability & Statistics / General
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