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Tools for Statistical Inference: Observed Data and Data Augmentation Methods: v. 67 (Lecture Notes in Statistics) - Softcover
Synopsis
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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- PublisherSpringer-Verlag Berlin and Heidelberg GmbH & Co. K
- Publication date1991
- ISBN 10 354097525X
- ISBN 13 9783540975250
- BindingPerfect Paperback
- LanguageEnglish
- Number of pages116
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Tools for statistical inference: Observed data and data augmentation methods (Lecture notes in statistics)
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