Testing heteroscedasticity in nonparametric regression models based on residual analysis

被引:4
|
作者
Zhang Lei [1 ,2 ]
Mei Chang-lin [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Sci, Xian 710049, Peoples R China
[2] Xinhua News Agcy, Beijing 100803, Peoples R China
基金
中国国家自然科学基金;
关键词
heteroscedasticity; nonparametric regression; residual analysis;
D O I
10.1007/s11766-008-1648-0
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The importance of detecting heteroscedasticity in regression analysis is widely recognized because efficient inference for the regression function requires that heteroscedasticity should be taken into account. In this paper, a simple test for heteroscedasticity is proposed in nonparametric regression based on residual analysis. Furthermore, some simulations with a comparison with Dette and Munk's method are conducted to evaluate the performance of the proposed test. The results demonstrate that the method in this paper performs quite satisfactorily and is much more powerful than Dette and Munk's method in some cases.
引用
收藏
页码:265 / 272
页数:8
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