NONPARAMETRIC KERNEL ESTIMATION IN COUNTING-PROCESSES WITH EXPLANATORY VARIABLES

• 成果类型: Article
• 署名作者: WELLS, MT
• 署名单位: Cornell University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• 发表日期: 1994
• 页码: 795801
• 关键词: DENSITY-ESTIMATION; regression

摘要

Cox's proportional hazards model assumes that the duration hazard rate factors into a product of a baseline hazard rate and a nonnegative function of explanatory variables. An estimate of the baseline hazard rate, hence also of overall hazard rate, is proposed, based on a smoothing procedure using a kernel function. It is shown that the proposed estimator is uniformly consistent and converges weakly to a Gaussian process. Bandwidth selection issues are also discussed.