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

✍ Scribed by Alan T.K. Wan; Anoop Chaturvedi

• Publisher: Elsevier Science
• Year: 2001
• Tongue: English
• Weight: 167 KB
• Volume: 79
• Category: Article
• ISSN: 0047-259X
• DOI: 10.1006/jmva.2000.1963

✦ Synopsis

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.