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Open AccessJournal ArticleDOI

On Bayes Procedures for a Problem with Choice of Observations

T. W. Anderson
- 01 Sep 1964 - 
- Vol. 35, Iss: 3, pp 1128-1135
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This article is published in Annals of Mathematical Statistics.The article was published on 1964-09-01 and is currently open access. It has received 7 citations till now. The article focuses on the topics: Bayes classifier & Naive Bayes classifier.

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Journal ArticleDOI

Sequential Analysis with Delayed Observations

TL;DR: In this article, the authors considered a special case of the situation in which after the decision to stop observation is made a fixed number of additional observations are available for the terminal decision, and the test is then based on the ratio of the likelihoods (at two simple hypotheses) of all the observations (whatever stopping rule is used).
Book ChapterDOI

Theories and methods in classification: a review

TL;DR: In this paper, the authors present a general theory regarding classification into known distributions, rules based on ranks, rules on tolerance regions and distance between empirical CDFs, nearest neighbor rules, rules with density estimates, nonparametric or distribution-free methods, classification into more than two multivariate normal populations with different covariance matrices, compounddecision and empirical Bayes approaches, and general theory of classification when the information about the distribution is based on samples.
Book ChapterDOI

Bibliographie zur statistischen Entscheidungstheorie 1950–1967 / Bibliography of Statistical Decision Theory 1950–1967

TL;DR: This bibliographie zur statistischen entscheidungstheorie 19501967 bibliography of statistical decision theory19501967%0D is among them and can be your companion.

An Exposition on Bayesian Inference

John Laffoon
TL;DR: This chapter discusses Bayes Bayesian Regression, a method for estimating the likelihood of an event being Bayesian on the basis of a prior distribution of events.
References
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An Introduction to Multivariate Statistical Analysis

TL;DR: In this article, the distribution of the Mean Vector and the Covariance Matrix and the Generalized T2-Statistic is analyzed. But the distribution is not shown to be independent of sets of Variates.
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