Open Access
March, 1987 On Testing Whether New is Better Than Used Using Randomly Censored Data
Yoshiki Kumazawa
Ann. Statist. 15(1): 420-426 (March, 1987). DOI: 10.1214/aos/1176350276

Abstract

Under a model of random censorship, we consider the test $H_0$: a life distribution is exponential, versus $H_1$: it is new better than used, but not exponential. This paper introduces a class of tests by using the Kaplan-Meier estimator for the sample distribution in the uncensored model. Under some regularity conditions, the asymptotic normality of statistics is derived by an application of von Mises' method, and asymptotically valid tests are obtained by using estimators for the null standard deviations. The efficiency loss in the proportional censoring model is studied and a Monte Carlo study of power is performed.

Citation

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Yoshiki Kumazawa. "On Testing Whether New is Better Than Used Using Randomly Censored Data." Ann. Statist. 15 (1) 420 - 426, March, 1987. https://doi.org/10.1214/aos/1176350276

Information

Published: March, 1987
First available in Project Euclid: 12 April 2007

zbMATH: 0613.62123
MathSciNet: MR885747
Digital Object Identifier: 10.1214/aos/1176350276

Subjects:
Primary: 62N05
Secondary: 62G10

Keywords: counting process , efficiency loss , Kaplan-Meier estimator , von Mises' statistical functional

Rights: Copyright © 1987 Institute of Mathematical Statistics

Vol.15 • No. 1 • March, 1987
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