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Title: Reference points based transformation and approximation (English)
Author: Török, Csaba
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 49
Issue: 4
Year: 2013
Pages: 644-662
Summary lang: English
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Category: math
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Summary: Interpolating and approximating polynomials have been living separately more than two centuries. Our aim is to propose a general parametric regression model that incorporates both interpolation and approximation. The paper introduces first a new $r$-point transformation that yields a function with a simpler geometrical structure than the original function. It uses $r \geq 2$ reference points and decreases the polynomial degree by $r-1$. Then a general representation of polynomials is proposed based on $r \geq 1$ reference points. The two-part model, which is suited to piecewise approximation, consist of an ordinary least squares polynomial regression and a reparameterized one. The later is the central component where the key role is played by the reference points. It is constructed based on the proposed representation of polynomials that is derived using the $r$-point transformation $T_r(x)$. The resulting polynomial passes through $r$ reference points and the other points approximates. Appropriately chosen reference points ensure quasi smooth transition between the two components and decrease the dimension of the LS normal matrix. We show that the model provides estimates with such statistical properties as consistency and asymptotic normality. (English)
Keyword: polynomial representation
Keyword: approximation model
Keyword: smooth connection
Keyword: consistency
Keyword: asymptotic normality
MSC: 41A10
MSC: 62F12
MSC: 62J05
MSC: 65D05
MSC: 65D07
MSC: 65D10
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Date available: 2013-09-17T16:34:20Z
Last updated: 2013-09-17
Stable URL: http://hdl.handle.net/10338.dmlcz/143451
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