ON THE LEAST-SQUARES CROSS-VALIDATION BANDWIDTH IN HAZARD RATE ESTIMATION

• 成果类型: Article
• 署名作者: PATIL, PN
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176349398
• 发表日期: 1993
• 页码: 1792-1810
• 关键词: density estimators; censored-data; selection; error

摘要

It is known that the least squares cross-validation bandwidth is asymptotically optimal in the case of kernel-based density and hazard rate estimation in the settings of both complete and randomly right-censored samples. From a practical point of view, it is important to know at what rate the cross-validation bandwidth converges to the optimal. In this paper we answer this question in a general setup which unifies all four possible cases.