Employing Robust MM-estimators in Estimating Principal Component Regression Model - A Comparative Study-

Section: Research Paper
Issue
Vol. 18 No. 1 (2021): Volume 18 Issue 1
Published
Jun 25, 2025
Pages
74-87

Abstract

This paper focuses on proposing the use of robust MM estimators in estimating the parameters of the principal component regression model, which is usually used in estimating the regression model when the explanatory variables are not independent. even in the presence of leverage points in the data and gives estimators with good efficiency, this estimator has been called the MM estimator, referring to the fact that more than one M estimator is used to obtain the final estimator as the estimation is done using the Iteratively Re-weighted Least Square (IRLS) method

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Authors

Bashar Abd Al-Aziz Al-Talib

Department of Statistics and Informatics, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq

ORCID
G. M. Aldabagh

Software Department, College of Computer Sciences and Mathematics, University of Mosul, Mosul / Iraq

ORCID

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How to Cite

Abd Al-Aziz Al-Talib, B., بشار, M. Aldabagh, G., & إسراء. (2025). Employing Robust MM-estimators in Estimating Principal Component Regression Model - A Comparative Study-. IRAQI JOURNAL OF STATISTICAL SCIENCES, 18(1), 74–87. Retrieved from https://rjps.uomosul.edu.iq/index.php/stats/article/view/20667