Optimal Generalized Biased Estimator in Linear Regression Model

Sivarajah Arumairajan; Pushpakanthie Wijekoon

doi:10.4236/ojs.2015.55042

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Open Journal of Statistics > Vol.5 No.5, August 2015

Optimal Generalized Biased Estimator in Linear Regression Model ()

Sivarajah Arumairajan^1,2, Pushpakanthie Wijekoon³

¹Postgraduate Institute of Science, University of Peradeniya, Peradeniya, Sri Lanka.
²Department of Mathematics and Statistics, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka.
³Department of Statistics & Computer Science, Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka.

DOI: 10.4236/ojs.2015.55042 PDF HTML XML 2,590 Downloads 3,388 Views Citations

Abstract

The paper introduces a new biased estimator namely Generalized Optimal Estimator (GOE) in a multiple linear regression when there exists multicollinearity among predictor variables. Stochastic properties of proposed estimator were derived, and the proposed estimator was compared with other existing biased estimators based on sample information in the the Scalar Mean Square Error (SMSE) criterion by using a Monte Carlo simulation study and two numerical illustrations.

Keywords

Multicollinearity, Biased Estimator, Generalized Optimal Estimator, Scalar Mean Square Error

Share and Cite:

Arumairajan, S. and Wijekoon, P. (2015) Optimal Generalized Biased Estimator in Linear Regression Model. Open Journal of Statistics, 5, 403-411. doi: 10.4236/ojs.2015.55042.

Conflicts of Interest

The authors declare no conflicts of interest.

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