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Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki, 2016, Volume 56, Number 2, Pages 202–207
DOI: https://doi.org/10.7868/S0044466916020083 (Mi zvmmf10337) 		 
This article is cited in 5 scientific papers (total in 5 papers)

Solution of the linear regression problem using matrix correction methods in the $l_1$ metric

V. A. Gorelika, O. S. Trembacheva (Barkalova)b

a Dorodnicyn Computing Center, Russian Academy of Sciences, ul. Vavilova 40, Moscow, 119333, Russia
b Moscow State Pedagogical University, ul. Malaya Pirogovskaya 1, Moscow, 119882, Russia
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DOI: https://doi.org/10.7868/S0044466916020083
Abstract: The linear regression problem is considered as an improper interpolation problem. The metric $l_1$ is used to correct (approximate) all the initial data. A probabilistic justification of this metric in the case of the exponential noise distribution is given. The original improper interpolation problem is reduced to a set of a finite number of linear programming problems. The corresponding computational algorithms are implemented in MATLAB.
Key words: data processing, regression problem, matrix correction, maximum likelihood method, exponential distribution.
Funding agency Grant number
Ministry of Education and Science of the Russian Federation 01201153724
Received: 12.05.2015
English version:
Computational Mathematics and Mathematical Physics, 2016, Volume 56, Issue 2, Pages 200–205
DOI: https://doi.org/10.1134/S0965542516020081
Bibliographic databases:
Document Type: Article
UDC: 519.61
Language: Russian
Citation: V. A. Gorelik, O. S. Trembacheva (Barkalova), “Solution of the linear regression problem using matrix correction methods in the $l_1$ metric”, Zh. Vychisl. Mat. Mat. Fiz., 56:2 (2016), 202–207; Comput. Math. Math. Phys., 56:2 (2016), 200–205
Citation in format AMSBIB
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    • This publication is cited in the following 5 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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