Boosting kernel density estimates: A bias reduction technique?

• 成果类型: Article
• 署名作者: Di Marzio, M; Taylor, CC
• 署名单位: G d'Annunzio University of Chieti-Pescara; University of Leeds
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/91.1.226
• 发表日期: 2004
• 页码: 226233
• 关键词: additive logistic-regression; statistical view

摘要

This paper proposes an algorithm for boosting kernel density estimates. We show that boosting is closely linked to a previously proposed method of bias reduction and indicate how it should enjoy similar properties. Numerical examples and simulations are used to illustrate the findings, and we also suggest further areas of research.