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Linearized models with constraints of type I
Applications of Mathematics, Tome 48 (2003) no. 2, pp. 81-95 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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In nonlinear regression models with constraints a linearization of the model leads to a bias in estimators of parameters of the mean value of the observation vector. Some criteria how to recognize whether a linearization is possible is developed. In the case that they are not satisfied, it is necessary to decide whether some quadratic corrections can make the estimator better. The aim of the paper is to contribute to the solution of the problem.
In nonlinear regression models with constraints a linearization of the model leads to a bias in estimators of parameters of the mean value of the observation vector. Some criteria how to recognize whether a linearization is possible is developed. In the case that they are not satisfied, it is necessary to decide whether some quadratic corrections can make the estimator better. The aim of the paper is to contribute to the solution of the problem.
DOI : 10.1023/A:1026038009693
Classification : 62F10, 62J02, 62J05
Keywords: nonlinear regression model with constraints; linearization; quadratization 
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     title = {Linearized models with constraints of type {I}},
     journal = {Applications of Mathematics},
     pages = {81--95},
     year = {2003},
     volume = {48},
     number = {2},
     doi = {10.1023/A:1026038009693},
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     url = {http://geodesic.mathdoc.fr/articles/10.1023/A:1026038009693/}
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Kubáček, Lubomír. Linearized models with constraints of type I. Applications of Mathematics, Tome 48 (2003) no. 2, pp. 81-95. doi: 10.1023/A:1026038009693

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