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Statistical decision theory and bayesian analysis James O. Berger
Publisher: Springer

Solodovnikov, Introduction to the Statistical Dynamics of Automatic Control Systems, Dover, 1960. Statistical Decision Theory and Bayesian Analysis ISBN: 0387960988 | edition 1985 | File type: PDF | 624 pages | 20,3 mb. Chen, Approximate Kalman Filtering, World Scientific, 1993. First, Jim has contributed and is contributing immensely to statistical science from many respects, first and foremost in grounding Bayesian analysis within decision theory. For inference, a full report of the posterior distribution is the correct and final conclusion of a statistical analysis. Game theory isn't used all that much for adaptive clinical trials except in the form of statistical decision theory. Van der Linde, “Bayesian Measures of Model Complexity and Fit,” J. A special very important problem of the statistical machine learning is the classification problem which can be regarded as a task of classifying some objects into classes in accordance with their properties or features. However, this may be impractical, particularly when the posterior is high-dimensional. Berger, Statistical Decision Theory and Bayesian Analysis, second ed. A list of references on Bayesian Title: Statistical Decision Theory and Bayesian Analysis Author: James O. One of the directions for developing the corresponding methods is the fuzzy classification which applies the main ideas of fuzzy set theory to various classification problems. While an innocuous theory, practical use of the Bayesian approach requires consideration of complex practical issues, including the source of the prior distribution, the choice of a likelihood function, computation and summary of the posterior .