Geodesic
Seemingly unrelated regression models
Applications of Mathematics, Tome 58 (2013) no. 1, pp. 111-123 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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The cross-covariance matrix of observation vectors in two linear statistical models need not be zero matrix. In such a case the problem is to find explicit expressions for the best linear unbiased estimators of both model parameters and estimators of variance components in the simplest structure of the covariance matrix. Univariate and multivariate forms of linear models are dealt with.
The cross-covariance matrix of observation vectors in two linear statistical models need not be zero matrix. In such a case the problem is to find explicit expressions for the best linear unbiased estimators of both model parameters and estimators of variance components in the simplest structure of the covariance matrix. Univariate and multivariate forms of linear models are dealt with.
DOI : 10.1007/s10492-013-0005-7
Classification : 62F10, 62H12, 62J05, 62P20
Keywords: seemingly unrelated regression; linear statistical model; variance components; BLUE; MINQUE 
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Kubáček, Lubomír. Seemingly unrelated regression models. Applications of Mathematics, Tome 58 (2013) no. 1, pp. 111-123. doi: 10.1007/s10492-013-0005-7

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