The Annals of Mathematical Statistics

Likelihood Ratio Tests for Sequential $k$-Decision Problems

Gary Lorden

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Sequential tests of separated hypotheses concerning the parameter $\theta$ of a Koopman-Darmois family are studied from the point of view of minimizing expected sample sizes pointwise in $\theta$ subject to error probability bounds. Sequential versions of the (generalized) likelihood ratio test are shown to exceed the minimum expected sample sizes by at most $M \log \log \underline{\alpha}^{-1}$ uniformly in $\theta$, where $\underline{\alpha}$ is the smallest error probability bound. The proof considers the likelihood ratio tests as ensembles of sequential probability ratio tests and compares them with alternative procedures by constructing alternative ensembles, applying a simple inequality of Wald and a new inequality of similar type. A heuristic approximation is given for the error probabilities of likelihood ratio tests, which provides an upper bound in the case of a normal mean.

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Ann. Math. Statist., Volume 43, Number 5 (1972), 1412-1427.

First available in Project Euclid: 27 April 2007

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Lorden, Gary. Likelihood Ratio Tests for Sequential $k$-Decision Problems. Ann. Math. Statist. 43 (1972), no. 5, 1412--1427. doi:10.1214/aoms/1177692374.

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