Geodesic
On a linearization of regression models
Applications of Mathematics, Tome 40 (1995) no. 1, pp. 61-78

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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.
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.
DOI : 10.21136/AM.1995.134279
Classification : 62J02, 62J05
Keywords: nonlinear regression model; linearization; parameter effect curvature; intrinsic curvature 
Kubáček, Lubomír. On a linearization of regression models. Applications of Mathematics, Tome 40 (1995) no. 1, pp. 61-78. doi: 10.21136/AM.1995.134279
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