Title of article
Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model
Author/Authors
Lukman, Adewale F Department of Physical Sciences - Landmark University - Omu-Aran - Nigeria , Ayinde, Kayode Department of Statistics - Federal University of Technology - Akure - Nigeria , Golam Kibria, B. M Department of Mathematics and Statistics - Florida International University - Miami - FL - USA , Jegede, Segun L Department of Physical Sciences - Landmark University - Omu-Aran - Nigeria
Pages
24
From page
1
To page
24
Abstract
The general linear regression model has been one of the most frequently used models over the years, with the ordinary least squares estimator (OLS) used to estimate its parameter. The problems of the OLS estimator for linear regression analysis include that of multicollinearity and outliers, which lead to unfavourable results. This study proposed a two-parameter ridge-type modified M-estimator (RTMME) based on the M-estimator to deal with the combined problem resulting from multicollinearity and outliers. Through theoretical proofs, Monte Carlo simulation, and a numerical example, the proposed estimator outperforms the modified ridge-type estimator and some other considered existing estimators.
Keywords
Parameter Modified Ridge , Type M-Estimator , Linear Regression Model
Journal title
The Scientific World Journal
Serial Year
2020
Record number
2615855
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