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

Chien-Chia L. Huang, Yow-Jen Jou and Hsun-Jung Cho

Journal of Applied Statistics, 2017, vol. 44, issue 12, 2161-2171

Abstract: 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.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:44:y:2017:i:12:p:2161-2171

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DOI: 10.1080/02664763.2016.1247790

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