Estimating Heteroscedastic Variances in Linear Models
โ Scribed by Horn, Susan D.; Horn, Roger A.; Duncan, David B.
- Book ID
- 121399132
- Publisher
- American Statistical Association
- Year
- 1975
- Tongue
- English
- Weight
- 531 KB
- Volume
- 70
- Category
- Article
- ISSN
- 0162-1459
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Estimation of parameters in linear fixed and mixed effects models, under order restrictions on the error variances, is considered in this article. For simplicity of exposition, we shall assume that the error variances are subject to simple order restriction. Similar methodology can be developed for
Two types of recursive estimators are developed for the variance components 2 and 2 of the dynamic linear model: non-Bayesian and Bayesian. From a frequentist point of view, both types of estimators are mean square consistent. The non-Bayesian estimator of 2 is also unbiased.
In mixed linear models with two variance components, classes of estimators improving on ANOVA estimators for the variance components and the ratio of variances are constructed on the basis of the invariant statistics. Out of the classes, consistent, improved and positive estimators are singled out.