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Bayesian-Ridge Estimator For Linear Regression Model

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  • Usman, Idowu

Abstract

Multicollinearity is a problem associated with inter-dependence of explanatory variables in linear regression model. The inefficiency of the Ordinary Least Square (OLS) Estimator lead to development of various other methods which include the Ridge Regression (RR) estimator and the Bayesian Regression (BREG) estimator. In this research, a new method of estimation called the Bayesian-Ridge Estimator (BRE) was proposed. Monte-Carlo experiments were conducted to examine and compare the performance of the proposed estimator with some other existing ones. Result shows that the proposed estimator is most efficient. Real life data sets were used to support the findings in the study.

Suggested Citation

  • Usman, Idowu, 2023. "Bayesian-Ridge Estimator For Linear Regression Model," OSF Preprints jn54r_v1, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:jn54r_v1
    DOI: 10.31219/osf.io/jn54r_v1
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