Displaying similar documents to “Estimation of the first order parameters in the twoepoch linear model”

Inversion of 3 × 3 partitioned matrices in investigation of the twoepoch linear model with the nuisance parameters

Karel Hron (2006)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

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The estimation procedures in the multiepoch (and specially twoepoch) linear regression models with the nuisance parameters that were described in [2], Chapter 9, frequently need finding the inverse of a 3 × 3 partitioned matrix. We use different kinds of such inversion in dependence on simplicity of the result, similarly as in well known Rohde formula for 2 × 2 partitioned matrix. We will show some of these formulas, also methods how to get the other formulas, and then we applicate the formulas...

Seemingly unrelated regression models

Lubomír Kubáček (2013)

Applications of Mathematics

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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.

Variance components and an additional experiment

Lubomír Kubáček (2012)

Applications of Mathematics

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Estimators of parameters of an investigated object can be considered after some time as insufficiently precise. Therefore, an additional measurement must be realized. A model of a measurement, taking into account both the original results and the new ones, has a litle more complicated covariance matrix, since the variance components occur in it. How to deal with them is the aim of the paper.