AbstractThe paper consists of two parts. The first part deals with solutions to some optimization problems. The general problem is one of minimssing Tr AVA′U, where V and U are positive definite matrices when the elements of the matrix are subject to linear restrictions of the type AX = O or X′AX = O and trace AVi = pi, i = 1,…, k, or U1′AU1 + … + Uk′AUk = M.These results are used in determining Minimum Norm Quadratic Unbiased Estimators (MINQUE) of variance and covariance components in linear models. The present paper is a generalization of an earlier attempt by the author to obtain estimators of heteroscedastic variances in a regression model.The method is quite general, applicable to all experimental situations, and the computations are ...
This thesis is concerned with the problem of variance components estimation and its applications in ...
summary:The paper deals with a linear model with linear variance-covariance structure, where the lin...
summary:An estimation of the linear function of elements of unknown matrices in the covariance compo...
The paper consists of two parts. The first part deals with solutions to some optimization problems. ...
The paper consists of two parts. The first part deals with solutions to some optimization problems. ...
AbstractThe paper consists of two parts. The first part deals with solutions to some optimization pr...
We write a linear model in the form Y=Xβ+Uξ, where β is an unknown parameter and ξ is a hypothetical...
AbstractThe variance of a quadratic function of the random variables in a linear model is minimized ...
Let Y=Xβ + e be a Gauss-Markoff linear model such that E(e)=0 and D(e), the dispersion matrix o...
summary:The paper deals with modified minimax quadratic estimation of variance and covariance compon...
Starting with the general linear model Y=Xβ+ε where E(εε')=θ1V1+ ... +θpVp, the theory of minimum no...
AbstractFor the unknown positive parameter σ2 in a general linear model ℳ={y,Xβ,σ2Σ}, the two common...
In this thesis, we describe the method of MINQUE (C. R. Rao (1970)) and its various generalizations ...
AbstractEstimation of variance components in linear model theory is presented as an application of e...
The Minimum Norm Quadratic Unbiased Invariant Estimator of the estimable linear function of the unkn...
This thesis is concerned with the problem of variance components estimation and its applications in ...
summary:The paper deals with a linear model with linear variance-covariance structure, where the lin...
summary:An estimation of the linear function of elements of unknown matrices in the covariance compo...
The paper consists of two parts. The first part deals with solutions to some optimization problems. ...
The paper consists of two parts. The first part deals with solutions to some optimization problems. ...
AbstractThe paper consists of two parts. The first part deals with solutions to some optimization pr...
We write a linear model in the form Y=Xβ+Uξ, where β is an unknown parameter and ξ is a hypothetical...
AbstractThe variance of a quadratic function of the random variables in a linear model is minimized ...
Let Y=Xβ + e be a Gauss-Markoff linear model such that E(e)=0 and D(e), the dispersion matrix o...
summary:The paper deals with modified minimax quadratic estimation of variance and covariance compon...
Starting with the general linear model Y=Xβ+ε where E(εε')=θ1V1+ ... +θpVp, the theory of minimum no...
AbstractFor the unknown positive parameter σ2 in a general linear model ℳ={y,Xβ,σ2Σ}, the two common...
In this thesis, we describe the method of MINQUE (C. R. Rao (1970)) and its various generalizations ...
AbstractEstimation of variance components in linear model theory is presented as an application of e...
The Minimum Norm Quadratic Unbiased Invariant Estimator of the estimable linear function of the unkn...
This thesis is concerned with the problem of variance components estimation and its applications in ...
summary:The paper deals with a linear model with linear variance-covariance structure, where the lin...
summary:An estimation of the linear function of elements of unknown matrices in the covariance compo...