Date of Award

1988

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Information Systems and Decision Sciences (Business Administration)

First Advisor

Helmut Schneider

Abstract

The computation of the renewal function when the distribution function is completely known has received much attention in the literature. However, in many cases the form of the distribution function is unknown and has to be estimated nonparametrically. Several nonparametric estimators for the renewal function for complete data were suggested by Frees (1986) and Schneider et al. (1988). In many cases, however, censoring of the lifetime might occur. In this study, estimators of the renewal function based on randomly censored data is discussed. We introduce nonparametric estimators of the renewal function and show that the estimators compare well with a parametric estimator. Also, different lifetime distributions with different hazard rates and various censoring distributions were considered in a simulation study.

Pages

94

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