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Double k-Class Estimators in Regression Models with Non-spherical Disturbances

Alan Wan () and Anoop Chaturvedi ()

Journal of Multivariate Analysis, 2001, vol. 79, issue 2, 226-250

Abstract: In this paper, we consider a family of feasible generalised double k-class estimators in a linear regression model with non-spherical disturbances. We derive the large sample asymptotic distribution of the proposed family of estimators and compare its performance with the feasible generalized least squares and Stein-rule estimators using the mean squared error matrix and risk under quadratic loss criteria. A Monte-Carlo experiment investigates the finite sample behaviour of the proposed family of estimators.

Keywords: bias; dominance; large; sample; asymptotic; quadratic; loss; mean; squared; error; Monte-Carlo; simulation; risk (search for similar items in EconPapers)
Date: 2001
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