Weak nonlinearity of growth curve models

Lubomír Kubáček

Displaying similar documents to “Weak nonlinearity of growth curve models”

Linear versus quadratic estimators in linearized models

Lubomír Kubáček (2004)

Applications of Mathematics

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In nonlinear regression models an approximate value of an unknown parameter is frequently at our disposal. Then the linearization of the model is used and a linear estimate of the parameter can be calculated. Some criteria how to recognize whether a linearization is possible are developed. In the case that they are not satisfied, it is necessary to take into account either some quadratic corrections or to use the nonlinear least squares method. The aim of the paper is to find some criteria...

Problems of sensitiveness and linearization in a determination of isobestic points

Lubomír Kubáček, Eva Fišerová (2003)

Mathematica Slovaca

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Properly recorded estimate and confidence regions obtained by an approximate covariance operator in a special nonlinear model

Gejza Wimmer (1995)

Applications of Mathematics

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The properly recorded standard deviation of the estimator and the properly recorded estimate are introduced. Bounds for the locally best linear unbiased estimator and estimate and also confidence regions for a linearly unbiasedly estimable linear functional of unknown parameters of the mean value are obtained in a special structure of nonlinear regression model. A sufficient condition for obtaining the properly recorded estimate in this model is also given.

On an accuracy of change points

Lubomír Kubáček (2002)

Mathematica Slovaca

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On a linearization of regression models

Lubomír Kubáček (1995)

Applications of Mathematics

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An approximate value of a parameter in a nonlinear regression model is known in many cases. In such situation a linearization of the model is possible however it is important to recognize, whether the difference between the actual value of the parameter and the approximate value does not cause significant changes, e.g., in the bias of the estimator or in its variance, etc. Some rules suitable for a solution of this problem are given in the paper.