Bandwidth selection for a data sharpening estimator in nonparametric regression

JOURNAL OF MULTIVARIATE ANALYSIS

卷:100

Article

Naito, Kanta¹  Yoshizaki, Masahiro¹ 

[1] Shimane Univ, Dept Math, Matsue, Shimane 6908504, Japan

关键词: Bandwidth;    Bias reduction;    Data sharpening;    Kernel;    Nonparametric regression;    Plug-in method;   

DOI  :  10.1016/j.jmva.2008.12.016

来源: Elsevier

【 摘 要 】

This paper is concerned with data-based selection of the bandwidth for a data sharpening estimator in nonparametric regression. Two kinds of bandwidths are considered: a bandwidth vector which has a different bandwidth for each covariate, and a scalar bandwidth that is common for all covariates. A plug-in method is developed and its theoretical performance is fully investigated. The proposed plug-in method works efficiently in our simulation study. (c) 2009 Elsevier Inc. All rights reserved.

【 授权许可】

Free