Nonparametric Bayesian estimators for counting processes

• 成果类型: Article
• 署名作者: Kim, YD
• 署名单位: Hankuk University Foreign Studies
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1018031207
• 发表日期: 1999
• 页码: 562-588
• 关键词: models

摘要

This paper is concerned with nonparametric Bayesian inference of the Aalen's multiplicative counting process model. For a desired nonparametric prior distribution of the cumulative intensity function, a dass of Levy processes is considered, and it is shown that the class of Levy processes is conjugate for the multiplicative counting process model, and formulas for obtaining a posterior process are derived. Finally, our results are applied to several practically important models such as one point processes for right-censored data, Poisson processes and Markov processes.