A simple smooth backfitting method for additive models

• 成果类型: Article
• 署名作者: Mammen, Enno; Park, Byeong U.
• 署名单位: University of Mannheim; Seoul National University (SNU)
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/009053606000000696
• 发表日期: 2006
• 页码: 2252-2271
• 关键词: asymptotic properties; bandwidth selection; regression-models

摘要

In this paper a new smooth backfitting estimate is proposed for additive regression models. The estimate has the simple structure of Nadaraya-Watson smooth backfitting but at the same time achieves the oracle property of local linear smooth backfitting. Each component is estimated with the same asymptotic accuracy as if the other components were known.