Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4598601 | Linear Algebra and its Applications | 2016 | 26 Pages |
Abstract
This article is concerned with the predictions in linear mixed models under stochastic linear restrictions. Mixed and stochastic restricted ridge predictors are introduced by using Gilmour's approach. We also investigate assumptions that the variance parameters are not known under stochastic linear restrictions and attain estimators of variance parameters. Superiorities the linear combinations of the predictors are done in the sense of mean square error matrix criterion. Finally, a hypothetical data set is considered to illustrate the findings.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Algebra and Number Theory
Authors
Özge Kuran, M. Revan Özkale,