RELAXED BOUNDARY SMOOTHING SPLINES

• 成果类型: Article
• 署名作者: OEHLERT, GW
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176348516
• 发表日期: 1992
• 页码: 146-160
• 关键词: noisy data; regression

摘要

Ordinary smoothing splines have an integrated mean squared error which is dominated by bias contributions at the boundaries. When the estimated function has additional derivatives, the boundary contribution to the bias affects the asymptotic rate of convergence unless the derivatives of the estimated function meet the natural boundary conditions. This paper introduces relaxed boundary smoothing splines and shows that they obtain the optimal asymptotic rate of convergence without conditions on the boundary derivatives of the estimated function.