By Peter D. Hoff

  1. A self-contained advent to likelihood, exchangeability and Bayes’ rule offers a theoretical figuring out of the utilized fabric.

  2. Numerous examples with R-code that may be run "as-is" let the reader to accomplish the knowledge analyses themselves.

  3. The improvement of Monte Carlo and Markov chain Monte Carlo tools within the context of knowledge research examples presents motivation for those computational methods.

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A First Course in Bayesian Statistical Methods (Springer Texts in Statistics) by Peter D. Hoff

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