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Testing heteroscedasticity in nonparametric regression models based on residual analysis 被引量:1

Testing heteroscedasticity in nonparametric regression models based on residual analysis
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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. 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.
出处 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2008年第3期265-272,共8页 高校应用数学学报(英文版)(B辑)
基金 the National Natural Science Foundation of China (10531030)
关键词 HETEROSCEDASTICITY nonparametric regression residual analysis heteroscedasticity, nonparametric regression, residual analysis
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