Abstract #300139

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JSM 2003 Abstract #300139
Activity Number: 344
Type: Invited
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Noether Award Committee
Abstract - #300139
Title: Nonparametric Methods in Reliability and Survival Analysis
Author(s): Myles Hollander*+
Companies: Florida State University
Address: Dept. of Stats, Tallahassee, FL, 32306,
Keywords: reliability ; survival analysis ; Bayesian methods ; counting processes
Abstract:

Over the past 45 years, reliability and survival analysis, two broad areas with much overlap, have provided fertile grounds for the development of nonparametric methods. Many survival analysis methods have their roots in Kaplan and Meier's (1958) product-limit estimator and Cox's (1972) proportional hazards model. The consideration of large nonparametric classes of life distributions and their roles in reliability theory (Barlow and Roschan 1965, 1970) motivated the development of tests and estimators for those classes. Ferguson's (1973) Dirichlet process prior, Sethuraman's (Sethuraman and Tiwari 1982) constructive definition of that prior, and Gibbs sampling (Gelfand and Smith,1990) led to many nonparametric Bayesian methods. Aalen's (1975) use of counting processes in conjunction with martingale theory and stochastic integration and Efron'(1979) bootstrap have been extremely useful for creating new procedures. We highlight some of the developments and consider some current and future research.

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