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A self-contained introduction to probability, exchangeability and Bayes’ rule provides a theoretical understanding of the applied material.
-
Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses themselves.
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The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivation for these computational methods.
Author: Peter D. Hoff
Publisher: Springer New York
Publish Date: 2010-11-19
Edition: Softcover reprint of hardcover 1st ed. 2009
ISBN: 1441928286
ISBN 13: 9781441928283
Dimension: Length: 6.1 inches, Width: 0.64 inches, Height: 9.25 inches
Weight: Weight: 1.00089866948 pounds
Binding: Paperback
Pages: 272
-
A self-contained introduction to probability, exchangeability and Bayes’ rule provides a theoretical understanding of the applied material.
-
Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses themselves.
-
The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivation for these computational methods.
Author: Peter D. Hoff
Publisher: Springer New York
Publish Date: 2010-11-19
Edition: Softcover reprint of hardcover 1st ed. 2009
ISBN: 1441928286
ISBN 13: 9781441928283
Dimension: Length: 6.1 inches, Width: 0.64 inches, Height: 9.25 inches
Weight: Weight: 1.00089866948 pounds
Binding: Paperback
Pages: 272