The goal of this book is to provide a unified presentation of a variety of algorithms for likelihood and Bayesian inference. Two types of methods are considered: observed data and data augmentation methods. The observed data methods, which are applied directly to the likelihood or posterior inference, include maximum likelihood, Laplace expansion, Monte Carlo and importance sampling. The data augmentation methods rely on an augmentation of the data which simplifies the likelihood or posterior inference. These include EM, ...
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The goal of this book is to provide a unified presentation of a variety of algorithms for likelihood and Bayesian inference. Two types of methods are considered: observed data and data augmentation methods. The observed data methods, which are applied directly to the likelihood or posterior inference, include maximum likelihood, Laplace expansion, Monte Carlo and importance sampling. The data augmentation methods rely on an augmentation of the data which simplifies the likelihood or posterior inference. These include EM, Louis' modification of the EM, poor man's data augmentation, SIR and the Gibbs sampler.
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Add this copy of Tools for Statistical Inference: Observed Data and Data to cart. $28.01, good condition, Sold by Anybook rated 5.0 out of 5 stars, ships from Lincoln, UNITED KINGDOM, published 1991 by Springer-Verlag.
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Seller's Description:
This is an ex-library book and may have the usual library/used-book markings inside. This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item, 250grams, ISBN: 038797525X.
