AbstractThe notion of linear sufficiency for the whole set of estimable functions in the general Gauss–Markov model is extended to the estimation of any special set of estimable functions in a general growth curve model. Some general results with respect to the concept of linear sufficiency are obtained, from which a necessary and sufficient condition is established for a linear transformation, {F1,F2}, of the observation matrix Y to have the property that there exists a linear function of F1YF2′ which is the BLUE of the estimable functions K1BK2′
We analyze the identification and estimation of parameters β satisfying the incomplete linear moment...
AbstractIn this paper, first we make a maximal extension of the well-known Gauss–Markov Theorem (GMT...
It is well known that there were proved several necessary and sufficient conditions for the ordinary...
AbstractGauss–Markov estimator of X1BX′2 under a general growth curve model {Y,X1BX′2,V2⊗V1} is give...
AbstractNotions of linear sufficiency and quadratic sufficiency are of interest to some authors. In ...
AbstractThis paper provides further contributions to the theory of linear sufficiency and linear com...
AbstractIn the linear model Y = Xβ + u the question arises when a linear transformation z = Ly conta...
A linear statistic Fy is called linearly sufficient for the estimable parametric function of X*β und...
AbstractConsider a general linear model Y=Xβ+Z where CovZ may be known only partially. We investigat...
AbstractIn this paper, we study the characterization of admissible linear estimators of regression c...
AbstractSome necessary and sufficient conditions are given for two equalities of ordinary least-squa...
AbstractPuntanen et al. [J. Statist. Plann. Inference 88 (2000) 173] provided two matrix-based proof...
AbstractAn extended growth curve model is considered which, among other things, is useful when linea...
AbstractThis article completes and simplifies earlier results on the derivation of best linear, or a...
Consider a general linear model $Y=X\beta+Z$, where $\text{Cov}\,Z$ may be known only partially. We ...
We analyze the identification and estimation of parameters β satisfying the incomplete linear moment...
AbstractIn this paper, first we make a maximal extension of the well-known Gauss–Markov Theorem (GMT...
It is well known that there were proved several necessary and sufficient conditions for the ordinary...
AbstractGauss–Markov estimator of X1BX′2 under a general growth curve model {Y,X1BX′2,V2⊗V1} is give...
AbstractNotions of linear sufficiency and quadratic sufficiency are of interest to some authors. In ...
AbstractThis paper provides further contributions to the theory of linear sufficiency and linear com...
AbstractIn the linear model Y = Xβ + u the question arises when a linear transformation z = Ly conta...
A linear statistic Fy is called linearly sufficient for the estimable parametric function of X*β und...
AbstractConsider a general linear model Y=Xβ+Z where CovZ may be known only partially. We investigat...
AbstractIn this paper, we study the characterization of admissible linear estimators of regression c...
AbstractSome necessary and sufficient conditions are given for two equalities of ordinary least-squa...
AbstractPuntanen et al. [J. Statist. Plann. Inference 88 (2000) 173] provided two matrix-based proof...
AbstractAn extended growth curve model is considered which, among other things, is useful when linea...
AbstractThis article completes and simplifies earlier results on the derivation of best linear, or a...
Consider a general linear model $Y=X\beta+Z$, where $\text{Cov}\,Z$ may be known only partially. We ...
We analyze the identification and estimation of parameters β satisfying the incomplete linear moment...
AbstractIn this paper, first we make a maximal extension of the well-known Gauss–Markov Theorem (GMT...
It is well known that there were proved several necessary and sufficient conditions for the ordinary...