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Investigating the impact of multicollinearity on linear regression estimates / Adewoye Kunle Bayo … [et al.]

The study was to investigate the impact of multicollinearity on linear regression estimates. The study was guided by the following specific objectives, (i) to examine the asymptotic properties of estimators and (ii) to compare lasso, ridge, elastic net with Ordinary Least Squares (OLS). The study em...

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Main Authors: Bayo, Adewoye Kunle, Rafiu, Ayinla Bayo, Funmilayo, Aminu Titilope, Oluyemi, Onikola Isaac
Format: Article
Language:English
Published: Universiti Teknologi MARA 2021
Subjects:
Analytical methods used in the solution of physical problems
Online Access:http://ir.uitm.edu.my/id/eprint/47825/1/47825.pdf
http://ir.uitm.edu.my/id/eprint/47825/
https://mjoc.uitm.edu.my
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spelling my.uitm.ir.478252021-06-18T08:46:47Z http://ir.uitm.edu.my/id/eprint/47825/ Investigating the impact of multicollinearity on linear regression estimates / Adewoye Kunle Bayo … [et al.] Bayo, Adewoye Kunle Rafiu, Ayinla Bayo Funmilayo, Aminu Titilope Oluyemi, Onikola Isaac Analytical methods used in the solution of physical problems The study was to investigate the impact of multicollinearity on linear regression estimates. The study was guided by the following specific objectives, (i) to examine the asymptotic properties of estimators and (ii) to compare lasso, ridge, elastic net with Ordinary Least Squares (OLS). The study employed Monte-Carlo simulation to generate set of highly collinear and induced multicollinearity variables with sample sizes of 25, 50, 100, 150, 200, 250, 1000 as a source of data in this research work and the data was analyzed with lasso, ridge, elastic net and ordinary least squares using statistical package. The study findings revealed that absolute bias of ordinary least squares was consistent at all sample sizes as revealed by past researched on multicollinearity as well while lasso type estimators fluctuated alternately. Also revealed that, mean square error of ridge regression outperformed other estimators with minimum variance at small sample size and OLS was the best at large sample size. The study recommended that OLS was asymptotically consistent at a specified sample sizes on this research work and ridge regression was efficient at small and moderate sample size. Universiti Teknologi MARA 2021-01 Article PeerReviewed text en http://ir.uitm.edu.my/id/eprint/47825/1/47825.pdf ID47825 Bayo, Adewoye Kunle and Rafiu, Ayinla Bayo and Funmilayo, Aminu Titilope and Oluyemi, Onikola Isaac (2021) Investigating the impact of multicollinearity on linear regression estimates / Adewoye Kunle Bayo … [et al.]. Malaysian Journal of Computing (MJoC), 6 (1). pp. 698-714. ISSN (eISSN): 2600-8238 https://mjoc.uitm.edu.my
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Analytical methods used in the solution of physical problems
spellingShingle Analytical methods used in the solution of physical problems
Bayo, Adewoye Kunle
Rafiu, Ayinla Bayo
Funmilayo, Aminu Titilope
Oluyemi, Onikola Isaac
Investigating the impact of multicollinearity on linear regression estimates / Adewoye Kunle Bayo … [et al.]
description The study was to investigate the impact of multicollinearity on linear regression estimates. The study was guided by the following specific objectives, (i) to examine the asymptotic properties of estimators and (ii) to compare lasso, ridge, elastic net with Ordinary Least Squares (OLS). The study employed Monte-Carlo simulation to generate set of highly collinear and induced multicollinearity variables with sample sizes of 25, 50, 100, 150, 200, 250, 1000 as a source of data in this research work and the data was analyzed with lasso, ridge, elastic net and ordinary least squares using statistical package. The study findings revealed that absolute bias of ordinary least squares was consistent at all sample sizes as revealed by past researched on multicollinearity as well while lasso type estimators fluctuated alternately. Also revealed that, mean square error of ridge regression outperformed other estimators with minimum variance at small sample size and OLS was the best at large sample size. The study recommended that OLS was asymptotically consistent at a specified sample sizes on this research work and ridge regression was efficient at small and moderate sample size.
format Article
author Bayo, Adewoye Kunle
Rafiu, Ayinla Bayo
Funmilayo, Aminu Titilope
Oluyemi, Onikola Isaac
author_facet Bayo, Adewoye Kunle
Rafiu, Ayinla Bayo
Funmilayo, Aminu Titilope
Oluyemi, Onikola Isaac
author_sort Bayo, Adewoye Kunle
title Investigating the impact of multicollinearity on linear regression estimates / Adewoye Kunle Bayo … [et al.]
title_short Investigating the impact of multicollinearity on linear regression estimates / Adewoye Kunle Bayo … [et al.]
title_full Investigating the impact of multicollinearity on linear regression estimates / Adewoye Kunle Bayo … [et al.]
title_fullStr Investigating the impact of multicollinearity on linear regression estimates / Adewoye Kunle Bayo … [et al.]
title_full_unstemmed Investigating the impact of multicollinearity on linear regression estimates / Adewoye Kunle Bayo … [et al.]
title_sort investigating the impact of multicollinearity on linear regression estimates / adewoye kunle bayo … [et al.]
publisher Universiti Teknologi MARA
publishDate 2021
url http://ir.uitm.edu.my/id/eprint/47825/1/47825.pdf
http://ir.uitm.edu.my/id/eprint/47825/
https://mjoc.uitm.edu.my
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score 13.244368

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