Geodesic
Estimation of dispersion in nonlinear regression models with constraints
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica, Tome 43 (2004) no. 1, pp. 75-86 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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Dispersion of measurement results is an important parameter that enables us not only to characterize not only accuracy of measurement but enables us also to construct confidence regions and to test statistical hypotheses. In nonlinear regression model the estimator of dispersion is influenced by a curvature of the manifold of the mean value of the observation vector. The aim of the paper is to find the way how to determine a tolerable level of this curvature.
Dispersion of measurement results is an important parameter that enables us not only to characterize not only accuracy of measurement but enables us also to construct confidence regions and to test statistical hypotheses. In nonlinear regression model the estimator of dispersion is influenced by a curvature of the manifold of the mean value of the observation vector. The aim of the paper is to find the way how to determine a tolerable level of this curvature.
Classification : 62F10, 62H12, 62J02, 62J05, 65C60
Keywords: nonlinear regression model; linearization; estimation of dispersion 
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Kubáček, Lubomír; Tesaříková, Eva. Estimation of dispersion in nonlinear regression models with constraints. Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica, Tome 43 (2004) no. 1, pp. 75-86. http://geodesic.mathdoc.fr/item/AUPO_2004_43_1_a7/

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