summary:In the paper an explicit expression for the Bayes invariant quadratic unbiased estimate of the linear function of the variance components is presented for the mixed linear model $\bold{t=X\beta+\epsilon}$, $\bold{E(t)=X\beta}$, $\bold{D(t)=0_1U_1+0_2U_2}$ with the unknown variance componets in the normal case. The matrices $\bold{U_1}$, $\bold{U_2}$ may be singular. Applications to two examples of the analysis of variance are given
In this paper, a linear mixed model which has two random effects is broken up into two models. This ...
Let Y=Xβ + e be a Gauss-Markoff linear model such that E(e)=0 and D(e), the dispersion matrix o...
An unbalanced mixed linear model with two variance components is considered, one variance component ...
summary:In the paper necessary and sufficient conditions for the existence and an explicit expressio...
summary:In the paper an explicit expression for the Bayes invariant quadratic unbiased estimate of t...
summary:In the paper an explicit expression for the Bayes invariant quadratic unbiased estimate of t...
summary:In the paper necessary and sufficient conditions for the existence and an explicit expressio...
summary:In the paper necessary and sufficient conditions for the existence and an explicit expressio...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:The MINQUE of the linear function $\int'\vartheta$ of the unknown variance-components parame...
summary:The MINQUE of the linear function $\int'\vartheta$ of the unknown variance-components parame...
International audienceWe study a mixed linear model with two variance components. We suppose that on...
In this paper, a linear mixed model which has two random effects is broken up into two models. This ...
In this paper, a linear mixed model which has two random effects is broken up into two models. This ...
Let Y=Xβ + e be a Gauss-Markoff linear model such that E(e)=0 and D(e), the dispersion matrix o...
An unbalanced mixed linear model with two variance components is considered, one variance component ...
summary:In the paper necessary and sufficient conditions for the existence and an explicit expressio...
summary:In the paper an explicit expression for the Bayes invariant quadratic unbiased estimate of t...
summary:In the paper an explicit expression for the Bayes invariant quadratic unbiased estimate of t...
summary:In the paper necessary and sufficient conditions for the existence and an explicit expressio...
summary:In the paper necessary and sufficient conditions for the existence and an explicit expressio...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:The MINQUE of the linear function $\int'\vartheta$ of the unknown variance-components parame...
summary:The MINQUE of the linear function $\int'\vartheta$ of the unknown variance-components parame...
International audienceWe study a mixed linear model with two variance components. We suppose that on...
In this paper, a linear mixed model which has two random effects is broken up into two models. This ...
In this paper, a linear mixed model which has two random effects is broken up into two models. This ...
Let Y=Xβ + e be a Gauss-Markoff linear model such that E(e)=0 and D(e), the dispersion matrix o...
An unbalanced mixed linear model with two variance components is considered, one variance component ...