BAYESIAN-RIDGE ESTIMATOR FOR LINEAR REGRESSION MODEL

Idowu Usman

No jn54r, OSF Preprints from Center for Open Science

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.

Date: 2023-08-28
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:jn54r

DOI: 10.31219/osf.io/jn54r

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