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Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Stata's data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability. The book emphasizes practical data analysis from the Bayesian perspective and covers the selection of realistic priors, computational efficiency and speed, the assessment of…mehr

Produktbeschreibung
Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Stata's data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability. The book emphasizes practical data analysis from the Bayesian perspective and covers the selection of realistic priors, computational efficiency and speed, the assessment of convergence, the evaluation of models, and the presentation of results.
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Autorenporträt
John Thompson is professor of genetic epidemiology at the University of Leicester and has many years experience working as a biostatistician on epidemiological projects.