Download e-book for iPad: Applied Bayesian Hierarchical Methods by Peter D.,Congdon

By Peter D.,Congdon

ISBN-10: 1584887206

ISBN-13: 9781584887201

The use of Markov chain Monte Carlo (MCMC) tools for estimating hierarchical versions consists of complicated info buildings and is frequently defined as a innovative improvement. An intermediate-level remedy of Bayesian hierarchical types and their purposes, Applied Bayesian Hierarchical Methods demonstrates some great benefits of a Bayesian method of info units related to inferences for collections of similar devices or variables and in equipment the place parameters might be taken care of as random collections.

Emphasizing computational matters, the booklet offers examples of the next software settings: meta-analysis, info based in area or time, multilevel and longitudinal information, multivariate information, nonlinear regression, and survival time facts. For the labored examples, the textual content commonly employs the WinBUGS package deal, permitting readers to discover substitute probability assumptions, regression constructions, and assumptions on earlier densities. It additionally comprises BayesX code, that is quite valuable in nonlinear regression. to illustrate MCMC sampling from first rules, the writer comprises labored examples utilizing the R package.

Through illustrative info research and a spotlight to statistical computing, this e-book makes a speciality of the sensible implementation of Bayesian hierarchical equipment. It additionally discusses numerous matters that come up whilst utilising Bayesian options in hierarchical and random results models.

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Applied Bayesian Hierarchical Methods by Peter D.,Congdon

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