✦ LIBER ✦
Reduction of Linear Models Using Correct or Incorrect Prior Information
✍ Scribed by Dr. H. Toutenburg
- Publisher
- John Wiley and Sons
- Year
- 1985
- Tongue
- English
- Weight
- 307 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0323-3847
No coin nor oath required. For personal study only.
✦ Synopsis
S u n~ mary
When there is no prior knowledge on the parameter vector j of the linear model then the LSE is most favourable at least in the class of linear unbiased estimators. On the other hand, in many practical problems one has some gueseed estimate of j . Using this information leads to two-step estimation procedures which may or may not dominate the LSE with respect to MSE. The dominance depends on the degree of incorrectnees of the griessed parameter and is analyzed numerically for the w e of sample reduction.