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Kaciranlar, S., Sakallioglu, S., Akdeniz, F., Styan, G.P.H. and Werner, H.J. (1999) A New Biased Estimator in Linear Regression and a Detailed Analysis of the Widely Analyzed Dataset on Portland Cement. Sankhyā, Ser. B, 61, 443-459.

has been cited by the following article:

• TITLE: Optimal Generalized Biased Estimator in Linear Regression Model

  AUTHORS: Sivarajah Arumairajan, Pushpakanthie Wijekoon

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

  JOURNAL NAME: Open Journal of Statistics, Vol.5 No.5, August 5, 2015

  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.