| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 406.25 KB | Adobe PDF |
Advisor(s)
Abstract(s)
In this paper we present a treatment for the estimation of variance components and
estimable vectors in linear mixed models in which the relation matrices may not commute.
To overcome this difficulty, we partition the mixed model in sub-models using orthogonal
matrices. In addition, we obtain confidence regions and derive tests of hypothesis for the
variance components. A numerical example is included. There we illustrate the estimation
of the variance components using our treatment and compare the obtained estimates with
the ones obtained by the ANOVA method. Besides this, we also present the restricted and
unrestricted maximum likelihood estimates.
Description
Keywords
Inference Mixed models Variance components