UNBIASED ESTIMATION OF FUNCTIONALS UNDER RANDOM CENSORSHIP

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概要

• 論文の詳細を見る

• This paper is intended as an investigation of estimating functionals of a lifetime distribution F under right censorship. Functionals given by ∫φdF, where φ's are known F-integrable functions, are considered. The nonparametric maximum likelihood estimator of F is given by the Kaplan-Meier (KM) estimator F_n, where n is sample size. A natural estimator of ∫φdF is a KM integral, ∫φdF_n. However, it is known that KM integrals have serious biases for unbounded φ's. A representation of the KM integral in terms of the KM estimator of a censoring distribution is obtained. The representation may be useful not only to calculate the KM integral but also to characterize the KM integral from a point view of the censoring distribution and the biasedness. A class of unbiased estimators under the condition that the censoring distribution is known is considered, and the estimators are compared.

• 日本統計学会の論文

著者

• Suzukawa Akio

  Graduate School Of Economics And Business Administration Hokkaido University

関連論文

• UNBIASED ESTIMATION OF FUNCTIONALS UNDER RANDOM CENSORSHIP
• ASYMPTOTIC PROPERTIES OF AALEN-JOHANSEN INTEGRALS FOR COMPETING RISKS DATA
• AN APPROXIMATE LIKELIHOOD PROCEDURE FOR COMPETING RISKS DATA

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