Inference on coefficient function for varying-coefficient partially linear model

被引:1
|
作者
Feng, Jingyan [2 ]
Zhang, Riquan [1 ,2 ]
机构
[1] E China Normal Univ, Dept Stat, Shanghai 200241, Peoples R China
[2] Shanxi Datong Univ, Dept Math, Datong 037009, Peoples R China
基金
中国国家自然科学基金;
关键词
chi(2)-distribution; generalized likelihood ratio; optimal rate of convergence; varying-coefficient partially linear model; Wilks phenomenon; TIME-SERIES;
D O I
10.1007/s11424-012-0324-x
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
One important model in handling the multivariate data is the varying-coefficient partially linear regression model. In this paper, the generalized likelihood ratio test is developed to test whether its coefficient functions are varying or not. It is showed that the normalized proposed test follows asymptotically chi (2)-distribution and theWilks phenomenon under the null hypothesis, and its asymptotic power achieves the optimal rate of the convergence for the nonparametric hypotheses testing. Some simulation studies illustrate that the test works well.
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页码:1143 / 1157
页数:15
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