Abstract
The aim of this study is to improve the e0ciency of weighted least-squares estimates for a regression parameter. An iterative procedure, starting with an unbiased estimate other than the unweighted least-squares estimate, yields estimates which are asymptotically more e0cient than the feasible generalized least-squares estimate when errors are spherically distributed. The result has an application in the improvement of the Graybill-Deal estimate of the common mean of several normal populations.
| Original language | English |
|---|---|
| Pages (from-to) | 133-146 |
| Number of pages | 14 |
| Journal | Journal of Statistical Planning and Inference |
| Volume | 110 |
| Issue number | 1-2 |
| DOIs | |
| Publication status | Published - 2003 Jan 15 |
| Externally published | Yes |
Keywords
- Asymptotic variance
- Common mean
- Graybill-Deal estimate
- Heteroscedastic linear regression
- Iterative procedure
- Replication
- Spherical distribution
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics