Quadratic estimations in mixed linear models
Applications of Mathematics, Tome 36 (1991) no. 2, pp. 134-144

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MR Zbl
In the paper four types of estimations of the linear function of the variance components are presented for the mixed linear model $\bold{Y=X \beta + e}$ with expectation $E(\bold{Y)=X \beta}$ and covariance matrix $D(\bold{Y)=0_1V_1 + ... + 0_mV_m}$.
In the paper four types of estimations of the linear function of the variance components are presented for the mixed linear model $\bold{Y=X \beta + e}$ with expectation $E(\bold{Y)=X \beta}$ and covariance matrix $D(\bold{Y)=0_1V_1 + ... + 0_mV_m}$.
DOI : 10.21136/AM.1991.104450
Classification : 62F10, 62J10, 62J99
Keywords: mixed linear model; minimum norm quadratic estimation; variance components; first order fixed parameter unknowns; second order fixed parameter unknowns; invariant for translations
Varga, Štefan. Quadratic estimations in mixed linear models. Applications of Mathematics, Tome 36 (1991) no. 2, pp. 134-144. doi: 10.21136/AM.1991.104450
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