On Non-Parametric Testing, the Uniform Behaviour of the t-Test, and Related Problems

On Non-Parametric Testing, the Uniform Behaviour of the t-Test, and Related Problems

In this article, we revisit some problems in non-parametric hypothesis testing. First, we extend the classical result of Bahadur & Savage [Ann. Math. Statist. 25 (1956) 1115] to other testing problems, and we answer a conjecture of theirs. Other examples considered are testing whether or not the...

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Veröffentlicht in:Scandinavian Journal of Statistics. - Blackwell Publishers, 1974. - 31(2004), 4, Seite 567-584
1. Verfasser: Romano, Joseph P. (VerfasserIn)
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2004
Zugriff auf das übergeordnete Werk:Scandinavian Journal of Statistics
Schlagworte:asymptotically maximin confidence intervals hypothesis tests large sample theory Philosophy Mathematics
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520 |a In this article, we revisit some problems in non-parametric hypothesis testing. First, we extend the classical result of Bahadur & Savage [Ann. Math. Statist. 25 (1956) 1115] to other testing problems, and we answer a conjecture of theirs. Other examples considered are testing whether or not the mean is rational, testing goodness-of-fit, and equivalence testing. Next, we discuss the uniform behaviour of the classical t-test. For most non-parametric models, the Bahadur-Savage result yields that the size of the t-test is one for every sample size. Even if we restrict attention to the family of symmetric distributions supported on a fixed compact set, the t-test is not even uniformly asymptotically level α. However, the convergence of the rejection probability is established uniformly over a large family with a very weak uniform integrability type of condition. Furthermore, under such a restriction, the t-test possesses an asymptotic maximin optimality property. 
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