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Estimation of variance components in mixed linear models

Júlia Volaufová, Viktor Witkovský (1992)

Applications of Mathematics

The MINQUE of the linear function ' 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 0 , is given.

Estimators and tests for variance components in cross nested orthogonal designs

Miguel Fonseca, João Tiago Mexia, Roman Zmyślony (2003)

Discussiones Mathematicae Probability and Statistics

Explicit expressions of UMVUE for variance components are obtained for a class of models that include balanced cross nested random models. These estimators are used to derive tests for the nullity of variance components. Besides the usual F tests, generalized F tests will be introduced. The separation between both types of tests will be based on a general theorem that holds even for mixed models. It is shown how to estimate the p-value of generalized F tests.

Exact distribution for the generalized F tests

Miguel Fonseca, Joao Tiago Mexia, Roman Zmyślony (2002)

Discussiones Mathematicae Probability and Statistics

Generalized F statistics are the quotients of convex combinations of central chi-squares divided by their degrees of freedom. Exact expressions are obtained for the distribution of these statistics when the degrees of freedom either in the numerator or in the denominator are even. An example is given to show how these expressions may be used to check the accuracy of Monte-Carlo methods in tabling these distributions. Moreover, when carrying out adaptative tests, these expressions enable us to estimate...

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