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Research Article Open access CC BY 4.0

Performance of the New Ridge Regression Parameters

Mowafaq Muhammed Al-Kassab, Mohammed Qasim Al-Awjar

Journal of Advances in Mathematics and Computer Science · pp. 1–9 · Published 1 Jan 2020

10.9734/jamcs/2019/v34i530225

Abstract

A new approach is presented to find the ridge parameter k when the multiple regression model suffers from multicollinearity. This approach studied two cases, for the value k, scalar, and matrix. A comparison between this proposed ridge parameter and other well-known ridge parameters evaluated elsewhere, in terms of the mean squares error criterion, is given. Examples from several research papers are conducted to illustrate the optimality of this proposed ridge parameter k.

Least squares multicollinearity ridge parameters scalar vector matrix mean squared error.

Cited by 1

Using Ridge Regression to Estimate Factors Affecting the Number of Births. A Comparative Study

Mowafaq Muhammed Al-Kassab, Salisu Ibrahim · Springer Proceedings in Mathematics & Statistics · 2023

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