Model checks for parametric regression models

被引：1
|
作者：
Liebscher, Eckhard [1 ]
机构：
[1] Univ Appl Sci Merseburg, Dept Comp Sci & Commun Syst, D-06217 Merseburg, Germany
来源：
TEST | 2012年 / 21卷 / 01期
关键词：
Model checks; Fixed-design regression model; Nonparametric variance estimator; VARIANCE-FUNCTION ESTIMATION; GOODNESS-OF-FIT; NONPARAMETRIC REGRESSION; RESIDUAL VARIANCE; CONSISTENT TEST; LEAST-SQUARES; DIFFERENCE; ESTIMATORS; HETEROSCEDASTICITY; COVARIATE;
D O I：
10.1007/s11749-011-0239-1
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：
In the paper we deal with the problem of model selection among fixed-design regression models. We establish a new test that indicates whether or not the model fits the data. The test statistic is based on the difference between a parametric estimator for the model variance and a nonparametric difference-based estimator, see Hall et al. (Biometrika 77:521-528, 1990). The weights in the nonparametric estimator depend on n, and they are chosen by solving an optimisation problem in order to obtain a test with high power.
引用
收藏
页码：132 / 155
页数：24
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