Double k-class estimators in regression models with non-spherical disturbances
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 226-250 |
| Journal / Publication | Journal of Multivariate Analysis |
| Volume | 79 |
| Issue number | 2 |
| Publication status | Published - 2001 |
Link(s)
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. © 2001 Academic Press.
Research Area(s)
- Bias, Dominance, Large sample asymptotic, Mean squared error, Monte-Carlo simulation, Quadratic loss, Risk
Citation Format(s)
Double k-class estimators in regression models with non-spherical disturbances. / Wan, Alan T.K.; Chaturvedi, Anoop.
In: Journal of Multivariate Analysis, Vol. 79, No. 2, 2001, p. 226-250.
In: Journal of Multivariate Analysis, Vol. 79, No. 2, 2001, p. 226-250.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
