It is well known that there were proved several necessary and sufficient conditions for the ordinary least squares estimators (OLSE) to be the best linear unbiased estimators (BLUE) of the fixed effects in general linear models. The purpose of this article is to verify one of these conditions given by Zyskind [39, 40]: there exists a matrix Q such that X = XQ, where X and are the design matrix and the covariance matrix, respectively. It will be shown the accessibility of this condition in some multivariate growth-curve models, establishing the known result regarding the equality between OLSE and BLUE in this type of linear models
AbstractThe growth curve model (Potthoff and Roy, 1964) and an extension (von Rosen, 1989) are consi...
Best linear unbiased estimators (BLUE’s) are known to be optimal in many respects under normal assum...
In this article, we consider the partitioned linear model M12(V0)={y,X1β1+X2β2,V0} and the correspon...
On the equality of the ordinary least squares estimators and the best linear unbiased estimators in ...
New results in matrix algebra applied to the fundamental bordered matrix of linear estimation theory...
A broad definition is given of balanced data in mixed models. For all such models, it is shown that ...
In this paper we consider the linear model {y, Xβ, σ2V}, where X has full column rank. Denote the or...
AbstractNew results in matrix algebra applied to the fundamental bordered matrix of linear estimatio...
AbstractIn this paper, we propose a framework of outer product least squares for covariance (COPLS) ...
Let Y be a vector of random variables such that E(Y)=Xβ where β is a vector of unknown parameters an...
The field of statistics is becoming increasingly more important as the amount of data in the world g...
The field of statistics is becoming increasingly more important as the amount of data in the world g...
AbstractIn this paper, we study the characterization of admissible linear estimators of regression c...
AbstractEstimation of parameters in the classical Growth Curve model, when the covariance matrix has...
AbstractIn this paper, we propose a framework of outer product least squares for covariance (COPLS) ...
AbstractThe growth curve model (Potthoff and Roy, 1964) and an extension (von Rosen, 1989) are consi...
Best linear unbiased estimators (BLUE’s) are known to be optimal in many respects under normal assum...
In this article, we consider the partitioned linear model M12(V0)={y,X1β1+X2β2,V0} and the correspon...
On the equality of the ordinary least squares estimators and the best linear unbiased estimators in ...
New results in matrix algebra applied to the fundamental bordered matrix of linear estimation theory...
A broad definition is given of balanced data in mixed models. For all such models, it is shown that ...
In this paper we consider the linear model {y, Xβ, σ2V}, where X has full column rank. Denote the or...
AbstractNew results in matrix algebra applied to the fundamental bordered matrix of linear estimatio...
AbstractIn this paper, we propose a framework of outer product least squares for covariance (COPLS) ...
Let Y be a vector of random variables such that E(Y)=Xβ where β is a vector of unknown parameters an...
The field of statistics is becoming increasingly more important as the amount of data in the world g...
The field of statistics is becoming increasingly more important as the amount of data in the world g...
AbstractIn this paper, we study the characterization of admissible linear estimators of regression c...
AbstractEstimation of parameters in the classical Growth Curve model, when the covariance matrix has...
AbstractIn this paper, we propose a framework of outer product least squares for covariance (COPLS) ...
AbstractThe growth curve model (Potthoff and Roy, 1964) and an extension (von Rosen, 1989) are consi...
Best linear unbiased estimators (BLUE’s) are known to be optimal in many respects under normal assum...
In this article, we consider the partitioned linear model M12(V0)={y,X1β1+X2β2,V0} and the correspon...