ON OPTIMAL DATA-BASED BANDWIDTH SELECTION IN KERNEL DENSITY-ESTIMATION

• 成果类型: Article
• 署名作者: HALL, P; SHEATHER, SJ; JONES, MC; MARRON, JS
• 署名单位: University of New South Wales Sydney; Open University - UK; University of North Carolina; University of North Carolina Chapel Hill
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• 发表日期: 1991
• 页码: 263269
• 关键词: data-based algorithm; Cross-validation; window width; point

摘要

A bandwidth selection method is proposed for kernel density estimation. This is based on the straightforward idea of plugging estimates into the usual asymptotic representation for the optimal bandwidth, but with two important modifications. The result is a bandwidth selector with the, by nonparametric standards, extremely fast asymptotic rate of convergence of n-1/2, where n --> infinity denotes sample size. Comparison is given to other bandwidth selection methods, and small sample impact is investigated.