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Research Article | Open Access

Condition numbers of the generalized ridge regression and its statistical estimation

Jing Kong1Shaoxin Wang2( )
Qufu Mingde School, Qufu 273165, China
School of Statistics and Data Science, Qufu Normal University, Qufu 273165, China
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Abstract

In this paper, we considered the condition number theory of a new generalized ridge regression model. The explicit expressions of different types of condition numbers were derived to measure the ill-conditionness of the generalized ridge regression problem with respect to different circumstances. To overcome the computational difficulty of computing the exact value of the condition number, we employed the statistical condition estimation theory to design efficient condition number estimators, and the numerical examples were also given to illustrate its efficiency.

CLC number: 15A12, 15A60, 65F35

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AIMS Mathematics
Pages 4178-4193

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Cite this article:
Kong J, Wang S. Condition numbers of the generalized ridge regression and its statistical estimation. AIMS Mathematics, 2024, 9(2): 4178-4193. https://doi.org/10.3934/math.2024205

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Received: 28 November 2023
Revised: 31 December 2023
Accepted: 10 January 2024
Published: 15 February 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)