Difference-based matrix perturbation method for semi-parametric regression with multicollinearity

This paper addresses the collinearity problems in semi-parametric linear models. Under the difference-based settings, we introduce a new diagnostic, the difference-based variance inflation factor (DVIF), for detecting the presence of multicollinearity in semi-parametric models. The DVIF is then used...

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Bibliographic Details
Published inJournal of applied statistics Vol. 44; no. 12; pp. 2161 - 2171
Main Authors Huang, Chien-Chia L., Jou, Yow-Jen, Cho, Hsun-Jung
Format Journal Article
LanguageEnglish
Published Taylor & Francis 10.09.2017
Subjects
Biased estimation
collinearity
diagnostic
partial linear models
variance inflation factor
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Summary:This paper addresses the collinearity problems in semi-parametric linear models. Under the difference-based settings, we introduce a new diagnostic, the difference-based variance inflation factor (DVIF), for detecting the presence of multicollinearity in semi-parametric models. The DVIF is then used to device a difference-based matrix perturbation method for solving the problem. The electricities distribution data set is analyzed, and numerical evidences validate the effectiveness of the proposed method.
ISSN:0266-4763
1360-0532
DOI:10.1080/02664763.2016.1247790