Bootstrap confidence bands for regression curves and their derivatives

• 成果类型: Article
• 署名作者: Claeskens, G; Van Keilegom, I
• 署名单位: Texas A&M University System; Texas A&M University College Station; Universite Catholique Louvain
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 2003
• 页码: 1852-1884
• 关键词: quasi-likelihood functions; generalized linear-models; Nonparametric Regression; density; CONVERGENCE; deviations; smoothers; extremes

摘要

Confidence bands for regression curves and their first p derivatives are obtained via local pth order polynomial estimation. The method allows for multiparameter local likelihood estimation as well as other unbiased estimating equations. As an alternative to the confidence bands obtained by asymptotic distribution theory, we also study smoothed bootstrap confidence bands. Simulations illustrate the finite sample properties of the methodology.