This proven text provides an accessible introduction to the foundations and applications of Bayesian analysis. Broadening its scope to nonstatisticians, this edition concentrates more on hierarchical Bayesian modeling as implemented via MCMC methods and related data analytic techniques. It contains a reader-friendly introduction to hierarchical statistical modeling, a new chapter on Bayesian design that emphasizes Bayesian clinical trials, a completely revised and expanded section on ranking and histogram estimation, and a ...
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This proven text provides an accessible introduction to the foundations and applications of Bayesian analysis. Broadening its scope to nonstatisticians, this edition concentrates more on hierarchical Bayesian modeling as implemented via MCMC methods and related data analytic techniques. It contains a reader-friendly introduction to hierarchical statistical modeling, a new chapter on Bayesian design that emphasizes Bayesian clinical trials, a completely revised and expanded section on ranking and histogram estimation, and a new case study on infectious disease modeling and the 1918 flu epidemic. This edition includes new data examples, corresponding R and WinBUGS code, and exercises.
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