Use generalized linear models or generalized partially linear models?

被引:0
|
作者
Xinmin Li
Haozhe Liang
Wolfgang Härdle
Hua Liang
机构
[1] Qingdao University,School of Mathematics and Statistics
[2] University of Science and Technology of China,Department of Statistics and Finance
[3] Humboldt-Universität zu Berlin,Institut für Statistik und Ökonometrie
[4] George Washington University,Department of Statistics
来源
Statistics and Computing | 2023年 / 33卷
关键词
Backfitting; Generalized additive models; Goodness-of-fit; Penalized spline; Profile likelihood; Quasi-likelihood;
D O I
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中图分类号
学科分类号
摘要
We propose test statistics based on the penalized spline to decide between generalized linear models and generalized partially linear models. The numerical performance of the proposed statistics is comparable to that of their kernel-based competitors, which have been shown to be asymptotically normal in the literature (Härdle et al. in J Am Stat Assoc 93:1461–1474, 1998). We also numerically explore the possibility of using the proposed statistics for goodness of fit checking for GLM. The proposed proposed procedures are illustrated to analyze two datasets.
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