Bias-corrected confidence bands in nonparametric regression
成果类型：
Article
署名作者：
Xia, YC
署名单位：
University of Hong Kong
刊物名称：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
ISSN/ISSBN：
1369-7412
DOI：
10.1111/1467-9868.00155
发表日期：
1998
页码：
797-811
关键词：
摘要：
Bias-corrected confidence bands for general nonparametric regression models are considered. We use local polynomial fitting to construct the confidence bands and combine the cross-validation method and the plug-in method to select the bandwidths. Related asymptotic results are obtained. Our simulations show that confidence bands constructed by local polynomial fitting have much better coverage than those constructed by using the Nadaraya-Watson estimator. The results are also applicable to nonparametric autoregressive time series models.
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