Difference-based matrix perturbation method for semi-parametric regression with multicollinearity. Issue 12 (10th September 2017)

• Record Type: Journal Article
• Authors: Huang, Chien-Chia L.; Jou, Yow-Jen; Cho, Hsun-Jung
• Is Part Of: Journal of applied statistics. Volume 44:Issue 12(2017)
• Page Start: 2161
• Page End: 2171
• Publication Date: 2017-09-10
• Subjects: Biased estimation -- collinearity -- diagnostic -- partial linear models -- variance inflation factor; 62J12 -- 62J20; Statistics -- Periodicals; 519.5
• DOI: 10.1080/02664763.2016.1247790
• Languages: English
• ISSNs: 0266-4763

Abstract

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.