Tools for Statistical Inference
Observed Data and Data Augmentation Methods
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Beschreibung
From the reviews: The purpose of the book under review is to give a survey of methods for the Bayesian or likelihood-based analysis of data. The author distinguishes between two types of methods: the observed data methods and the data augmentation ones. The observed data methods are applied directly to the likelihood or posterior density of the observed data. The data augmentation methods make use of the special "missing" data structure of the problem. They rely on an augmentation of the data which simplifies the likelihood or posterior density. #Zentralblatt für Mathematik#
Autor*in
Martin A. Tanner
Themen in »Tools for Statistical Inference«
Monte Carlo method expectation–maximization algorithm generalized linear model latent class analysis likelihood statistical inference