Modified Ridge Regression With Cook’s Distance for Semiparametric Regression Models

Multicollinearity and influential cases in semiparametric regression models lead to biased and unreliable estimates distorting leverage and residual patterns. To address these challenges, we propose modified penalized least squares estimators (MPLSEs). We use Cook’s distance and a case deletion appr...

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Main Authors: Najeeb Mahmood Khan, Muhammad Aman Ullah, Javaria Ahmad Khan, Salman Raza
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/jom/3801827
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author Najeeb Mahmood Khan
Muhammad Aman Ullah
Javaria Ahmad Khan
Salman Raza
author_facet Najeeb Mahmood Khan
Muhammad Aman Ullah
Javaria Ahmad Khan
Salman Raza
author_sort Najeeb Mahmood Khan
collection DOAJ
description Multicollinearity and influential cases in semiparametric regression models lead to biased and unreliable estimates distorting leverage and residual patterns. To address these challenges, we propose modified penalized least squares estimators (MPLSEs). We use Cook’s distance and a case deletion approach to evaluate their performance. The effectiveness of MPLSEs is demonstrated through the Longley dataset, where Cook’s distance is applied to the estimated coefficients, fitted values, residuals, and leverages, using a modified ridge parameter. In addition, a Monte Carlo simulation examines the influence of Cook’s distance across varying levels of multicollinearity, influential observations, and sample sizes. We compare MPLSEs with penalized least squares estimators (PLSEs) to assess their relative performance. The results show that MPLSEs outperform existing methods, effectively managing multicollinearity even with influential points. Our study aims to propose and validate a robust approach for addressing the challenges of multicollinearity and influential observations in semiparametric regression models.
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institution Kabale University
issn 2314-4785
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spelling doaj-art-84e254863a08455cb14b453719ecb8292025-01-15T00:00:01ZengWileyJournal of Mathematics2314-47852025-01-01202510.1155/jom/3801827Modified Ridge Regression With Cook’s Distance for Semiparametric Regression ModelsNajeeb Mahmood Khan0Muhammad Aman Ullah1Javaria Ahmad Khan2Salman Raza3Department of StatisticsDepartment of StatisticsDepartment of StatisticsDepartment of Computer ScienceMulticollinearity and influential cases in semiparametric regression models lead to biased and unreliable estimates distorting leverage and residual patterns. To address these challenges, we propose modified penalized least squares estimators (MPLSEs). We use Cook’s distance and a case deletion approach to evaluate their performance. The effectiveness of MPLSEs is demonstrated through the Longley dataset, where Cook’s distance is applied to the estimated coefficients, fitted values, residuals, and leverages, using a modified ridge parameter. In addition, a Monte Carlo simulation examines the influence of Cook’s distance across varying levels of multicollinearity, influential observations, and sample sizes. We compare MPLSEs with penalized least squares estimators (PLSEs) to assess their relative performance. The results show that MPLSEs outperform existing methods, effectively managing multicollinearity even with influential points. Our study aims to propose and validate a robust approach for addressing the challenges of multicollinearity and influential observations in semiparametric regression models.http://dx.doi.org/10.1155/jom/3801827
spellingShingle Najeeb Mahmood Khan
Muhammad Aman Ullah
Javaria Ahmad Khan
Salman Raza
Modified Ridge Regression With Cook’s Distance for Semiparametric Regression Models
Journal of Mathematics
title Modified Ridge Regression With Cook’s Distance for Semiparametric Regression Models
title_full Modified Ridge Regression With Cook’s Distance for Semiparametric Regression Models
title_fullStr Modified Ridge Regression With Cook’s Distance for Semiparametric Regression Models
title_full_unstemmed Modified Ridge Regression With Cook’s Distance for Semiparametric Regression Models
title_short Modified Ridge Regression With Cook’s Distance for Semiparametric Regression Models
title_sort modified ridge regression with cook s distance for semiparametric regression models
url http://dx.doi.org/10.1155/jom/3801827
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