Covariance matrix elements estimation: special linear model without and with repeated measurement

Gejza Wimmer

Displaying similar documents to “Covariance matrix elements estimation: special linear model without and with repeated measurement”

Estimation in a special structure of the linear model

Gejza Wimmer (1993)

Mathematica Slovaca

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Locally best linear-quadratic estimators

Gejza Wimmer (1996)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

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Estimation of variance components in mixed linear models

Júlia Volaufová, Viktor Witkovský (1992)

Applications of Mathematics

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The MINQUE of the linear function $\int^{'} ϑ$ of the unknown variance-components parameter $ϑ$ in mixed linear model under linear restrictions of the type $𝐑 ϑ = c$ is defined and derived. As an illustration of this estimator the example of the one-way classification model with the restrictions $ϑ_{1} = k ϑ_{2}$ , where $k \geq 0$ , is given.

Modified minimax quadratic estimation of variance components

Viktor Witkovský (1998)

Kybernetika

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The paper deals with modified minimax quadratic estimation of variance and covariance components under full ellipsoidal restrictions. Based on the, so called, linear approach to estimation variance components, i. e. considering useful local transformation of the original model, we can directly adopt the results from the linear theory. Under normality assumption we can can derive the explicit form of the estimator which is formally find to be the Kuks–Olman type estimator.