Stein-rule estimation in mixed regression models
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 203-214 |
| Journal / Publication | Biometrical Journal |
| Volume | 42 |
| Issue number | 2 |
| Publication status | Published - 2000 |
Link(s)
Abstract
This paper considers a Stein-rule mixed regression estimator for estimating a normal linear regression model in the presence of stochastic linear constraints. We derive the small disturbance asymptotic bias and risk of the proposed estimator, and analytically compare its risk with other related estimators. A Monte-Carlo experiment investigates the empirical risk performance of the proposed estimator.
Research Area(s)
- Mixed regression, Monte-Carlo experiment, Risk, Small disturbance, Stein-rule
Citation Format(s)
Stein-rule estimation in mixed regression models. / Shalabh, ; Wan, Alan T.K.
In: Biometrical Journal, Vol. 42, No. 2, 2000, p. 203-214.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
