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JOURNALS // Sibirskii Zhurnal Industrial'noi Matematiki // Archive

Sib. Zh. Ind. Mat., 2013 Volume 16, Number 4, Pages 47–60 (Mi sjim804)

This article is cited in 3 papers

Robust estimation of nonlinear structural models

V. I. Denisov, A. Yu. Timofeeva, E. A. Khailenko, O. I. Buzmakova

Novosibirsk State Technical University, 20 Karl Marx av., 630073 Novosibirsk

Abstract: The problem of the identification of nonlinear errors-in-variables models with large observational errors in the explanatory variable is considered. On the basis of robust estimation methods, we propose a development of the algorithms of adjusted and total least squares is suggested. This enabled us to get a better precision of the reconstruction of the response in the presence of outliers in the sample. The proposed algorithms are used in constructing the Engel curve from the data of a budget survey. As a result we managed to make more correct conclusions about the behavior of households with income variation.

Keywords: structural relation, robust estimation, least-squares method, regression penalized spline, Engel curve, budget survey.

UDC: 519.23

Received: 04.07.2013


 English version:
Journal of Applied and Industrial Mathematics, 2014, 8:1, 28–39

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