Combining the unrestricted estimators into a single estimator and a simulation study on the unrestricted estimators


Ozkale M. R.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.82, no.5, pp.653-688, 2012 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 82 Issue: 5
  • Publication Date: 2012
  • Doi Number: 10.1080/00949655.2010.550293
  • Title of Journal : JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Page Numbers: pp.653-688

Abstract

The purpose of this paper is to combine several regression estimators (ordinary least squares (OLS), ridge, contraction, principal components regression (PCR), Liu, r - k and r - d class estimators) into a single estimator. The conditions for the superiority of this new estimator over the PCR, the r - k class, the r - d class, (beta) over cap (k, d), OLS, ridge, Liu and contraction estimators are derived by the scalar mean square error criterion and the estimators of the biasing parameters for this new estimator are examined. Also, a numerical example based on Hald data and a simulation study are used to illustrate the results.