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Testing the Hazard Rate, Part I

We consider a nonparametric survival model with random censoring. To test whether the hazard rate has a parametric form the unknown hazard rate is estimated by a kernel estimator. Based on a limit theorem stating the asymptotic normality of the quadratic distance of this estimator from the smoothed hypothesis an asymptotic ®-test is proposed. Since the test statistic depends on the maximum likelihood estimator for the unknown parameter in the hypothetical model properties of this parameter estimator are investigated. Power considerations complete the approach.

Identiferoai:union.ndltd.org:Potsdam/oai:kobv.de-opus-ubp:5151
Date January 2003
CreatorsLiero, Hannelore
PublisherUniversität Potsdam, Mathematisch-Naturwissenschaftliche Fakultät. Institut für Mathematik
Source SetsPotsdam University
LanguageEnglish
Detected LanguageEnglish
TypePreprint
Formatapplication/pdf
Rightshttp://opus.kobv.de/ubp/doku/urheberrecht.php

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