The scaled [alpha]-Winsorized estimate of exponential scale for censored data: an analysis based on two influence functions

Mara Tableman and Alix I. Gitelman

Statistics & Probability Letters, 2002, vol. 59, issue 2, 169-181

Abstract: A new view of the maximum likelihood estimator (MLE) of exponential scale for censored data is presented. This is done by adapting Reid's (Ann. Statist. 9 (1981) 78) approach for obtaining the two influence functions (IF) for the Kaplan-Meier estimate of the survival function; one for uncensored and one for censored data, respectively. The MLEs two IFs are derived. Via this analysis, we propose a new robust estimator, the scaled [alpha]-Winsorized estimator (WE). Under Type II censoring, the WE is the MLE and, hence, is asymptotically efficient in that case. Its two IFs are bounded; hence,WE is B-robust. Its breakdown point is [alpha]. A comparison is made with respect to asymptotic bias and mean square error at contaminated exponential and Weibull survival models.

Keywords: Bivariate; functionals; B-robust; Exponential; MLE; Random; censoring; von; Mises; expansion; Winsorized; mean (search for similar items in EconPapers)
Date: 2002
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