Optimal Generalized Biased Estimator in Linear Regression Model

Sivarajah Arumairajan; Pushpakanthie Wijekoon

doi:10.4236/ojs.2015.55042

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Optimal Generalized Biased Estimator in Linear Regression Model

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DOI: 10.4236/ojs.2015.55042 2,382 Downloads 3,084 Views Citations

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Sivarajah Arumairajan^1,2, Pushpakanthie Wijekoon³

Affiliation(s)

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.

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

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

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.

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