Efficient estimation for semivarying-coefficient models

• 成果类型: Article
• 署名作者: Xia, YC; Zhang, WY; Tong, H
• 署名单位: National University of Singapore; University of Kent; University of Hong Kong
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/91.3.661
• 发表日期: 2004
• 页码: 661681
• 关键词: regression; dimension; selection; ORDER

摘要

Motivated by two practical problems, we propose a new procedure for estimating a semivarying-coefficient model. Asymptotic properties are established which show that the bias of the parameter estimator is of order h(3) when a symmetric kernel is used, where h is the bandwidth, and the variance is of order n(-1) and efficient in the semiparametric sense. Undersmoothing is unnecessary for the root-n consistency of the estimators. Therefore, commonly used bandwidth selection methods can be employed. A model selection method is also developed. Simulations demonstrate how the proposed method works. Some insights are obtained into the two motivating problems by using the proposed models.