Empirical Bayes Estimation of a Distribution (Survival) Function from Right Censored Observations.
Abstract
This paper provides an empirical Bayes approach to the problem of nonparametric estimation of a distribution (or survival) function when the observations are censored on the right. The results use the notion of a Dirichlet process prior (Ferguson, 1973, Ann. Stat., 2, 209-230). The paper presents a generalization to the case of right censored observations of the rate result of an empirical Bayes nonparametric estimator of a distribution function of Korwar and Hollander ((1974, Tech. Rept. No. 288, Dept. of Statistics, Florida State University) in the uncensored case. The rate of asymptotic convergence to optimality is shown to be the best obtainable for the problem considered.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 1976
- Accession Number
- ADA024079
Entities
People
- J. Van Ryzin
- V. Susaria
Organizations
- University of Wisconsin–Madison