Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations

The goal of this research is to compare multiple linear regression coefficient estimations with multicollinearity. In order to quantify the effectiveness of estimations by the mean of average mean square error, the ordinary least squares technique (OLS), modified ridge regression method (MRR), and...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	O. G. Obadina, Adedayo Funmi Adedotuun, O. A. Odusanya
Formato:	article
Lenguaje:	EN
Publicado:	Nigerian Society of Physical Sciences 2021
Materias:	Ridge Estimation Multicollinearity Monte-Carlo Simulations Physics QC1-999
Acceso en línea:	https://doaj.org/article/6fae51ecbee940bd9c60bf2c4c0df6d4
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:6fae51ecbee940bd9c60bf2c4c0df6d4
record_format	dspace
spelling	oai:doaj.org-article:6fae51ecbee940bd9c60bf2c4c0df6d42021-11-30T12:19:09ZRidge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations10.46481/jnsps.2021.3042714-28172714-4704https://doaj.org/article/6fae51ecbee940bd9c60bf2c4c0df6d42021-11-01T00:00:00Zhttps://journal.nsps.org.ng/index.php/jnsps/article/view/304https://doaj.org/toc/2714-2817https://doaj.org/toc/2714-4704 The goal of this research is to compare multiple linear regression coefficient estimations with multicollinearity. In order to quantify the effectiveness of estimations by the mean of average mean square error, the ordinary least squares technique (OLS), modified ridge regression method (MRR), and generalized Liu-Kejian method (LKM) are compared (AMSE). For this study, the simulation scenarios are 3 and 5 independent variables with zero mean normally distributed random error of variance 1, 5, and 10, three correlation coefficient levels; i.e., low (0.2), medium (0.5), and high (0.8) are determined for independent variables, and all combinations are performed with sample sizes 15, 55, and 95 by Monte Carlo simulation technique for 1,000 times in total. As the sample size rose, the AMSE decreased. The MRR and LKM both outperformed the LSM. At random error of variance 10, the MRR is the most suitable for all circumstances. O. G. ObadinaAdedayo Funmi AdedotuunO. A. OdusanyaNigerian Society of Physical SciencesarticleRidge EstimationMulticollinearityMonte-CarloSimulationsPhysicsQC1-999ENJournal of Nigerian Society of Physical Sciences, Vol 3, Iss 4 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Ridge Estimation Multicollinearity Monte-Carlo Simulations Physics QC1-999
spellingShingle	Ridge Estimation Multicollinearity Monte-Carlo Simulations Physics QC1-999 O. G. Obadina Adedayo Funmi Adedotuun O. A. Odusanya Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations
description	The goal of this research is to compare multiple linear regression coefficient estimations with multicollinearity. In order to quantify the effectiveness of estimations by the mean of average mean square error, the ordinary least squares technique (OLS), modified ridge regression method (MRR), and generalized Liu-Kejian method (LKM) are compared (AMSE). For this study, the simulation scenarios are 3 and 5 independent variables with zero mean normally distributed random error of variance 1, 5, and 10, three correlation coefficient levels; i.e., low (0.2), medium (0.5), and high (0.8) are determined for independent variables, and all combinations are performed with sample sizes 15, 55, and 95 by Monte Carlo simulation technique for 1,000 times in total. As the sample size rose, the AMSE decreased. The MRR and LKM both outperformed the LSM. At random error of variance 10, the MRR is the most suitable for all circumstances.
format	article
author	O. G. Obadina Adedayo Funmi Adedotuun O. A. Odusanya
author_facet	O. G. Obadina Adedayo Funmi Adedotuun O. A. Odusanya
author_sort	O. G. Obadina
title	Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations
title_short	Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations
title_full	Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations
title_fullStr	Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations
title_full_unstemmed	Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations
title_sort	ridge estimation's effectiveness for multiple linear regression with multicollinearity: an investigation using monte-carlo simulations
publisher	Nigerian Society of Physical Sciences
publishDate	2021
url	https://doaj.org/article/6fae51ecbee940bd9c60bf2c4c0df6d4
work_keys_str_mv	AT ogobadina ridgeestimationseffectivenessformultiplelinearregressionwithmulticollinearityaninvestigationusingmontecarlosimulations AT adedayofunmiadedotuun ridgeestimationseffectivenessformultiplelinearregressionwithmulticollinearityaninvestigationusingmontecarlosimulations AT oaodusanya ridgeestimationseffectivenessformultiplelinearregressionwithmulticollinearityaninvestigationusingmontecarlosimulations
_version_	1718406627690807296

Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations

Ejemplares similares