Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model
Joint Authors
Kibria, B. M. Golam
Lukman, Adewale F.
Ayinde, Kayode
Jegede, Segun L.
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-24, 24 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-15
Country of Publication
Egypt
No. of Pages
24
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Lukman, Adewale F.& Ayinde, Kayode& Kibria, B. M. Golam& Jegede, Segun L.. 2020. Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model. The Scientific World Journal،Vol. 2020, no. 2020, pp.1-24.
https://search.emarefa.net/detail/BIM-1213855
Modern Language Association (MLA)
Lukman, Adewale F.…[et al.]. Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model. The Scientific World Journal No. 2020 (2020), pp.1-24.
https://search.emarefa.net/detail/BIM-1213855
American Medical Association (AMA)
Lukman, Adewale F.& Ayinde, Kayode& Kibria, B. M. Golam& Jegede, Segun L.. Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model. The Scientific World Journal. 2020. Vol. 2020, no. 2020, pp.1-24.
https://search.emarefa.net/detail/BIM-1213855
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1213855