Underparametrization in a regression model with constraints II

Lubomír Kubáček

Displaying similar documents to “Underparametrization in a regression model with constraints II”

Multistage regression model

Lubomír Kubáček (1986)

Aplikace matematiky

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Necessary and sufficient conditions are given under which the best linear unbiased estimator (BLUE) ${\hat{β}}_{i} (Y_{1}, \dots, Y_{i})$ is identical with the BLUE ${\hat{β}}_{i} ({\hat{β}}_{1}, \dots, {\hat{β}}_{i - 1}, Y_{i})$ ; $Y_{1} \dots, Y_{i}$ are subvectors of the random vector $Y$ in a general regression model $(Y, X β, \sum)$ , ${(β_{1}^{'}, \dots, β_{i}^{'})}^{'} = β$ a vector of unknown parameters; the design matrix $X$ having a special so called multistage struture and the covariance matrix $\sum$ are given.

One of the calibration problems

Lubomír Kubáček, Ludmila Kubáčková (1997)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

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Problems of an additional experiment

Lubomír Kubáček (2007)

Mathematica Slovaca

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On an accuracy of change points

Lubomír Kubáček (2002)

Mathematica Slovaca

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Iterative estimators of parameters in linear models with partially variant coefficients

Shaolin Hu, Karl Meinke, Rushan Chen, Ouyang Huajiang (2007)

International Journal of Applied Mathematics and Computer Science

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A new kind of linear model with partially variant coefficients is proposed and a series of iterative algorithms are introduced and verified. The new generalized linear model includes the ordinary linear regression model as a special case. The iterative algorithms efficiently overcome some difficulties in computation with multidimensional inputs and incessantly appending parameters. An important application is described at the end of this article, which shows that this new model is reasonable...