Testing lack of fit of regression models under heteroscedasticity

被引：5

作者：

Li, CS ^{[1
]}

机构：

[1] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA

来源：

CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 1999年 / 27卷 / 03期

关键词：

bandwidth selection; fit comparison test; kernel smoother; quasi-likelihood estimator;

D O I：

10.2307/3316106

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A test is proposed for assessing the lack of fit of heteroscedastic nonlinear regression models that is based on comparison of nonparametric kernel and parametric fits. A data-driven method is proposed for bandwidth selection using the asymptotically optimal bandwidth of the parametric null model which leads to a test that has a limiting normal distribution under the null hypothesis and is consistent against any fixed alternative. The resulting test is applied to the problem of testing the lack of fit of a generalized linear model.

引用

页码：485 / 496

页数：12

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