Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/103040
Title: Linear regression modeling in monitoring tasks based on the method of least absolute deviations
Authors: Tyrsin, A.
Azaryan, A.
Issue Date: 2021
Publisher: American Institute of Physics Inc.
Citation: Tyrsin A. Linear regression modeling in monitoring tasks based on the method of least absolute deviations / A. Tyrsin, A. Azaryan. — DOI 10.1063/5.0041859 // AIP Conference Proceedings. — 2021. — Vol. 2333. — 090013.
Abstract: Algorithm for the exact solution of the problem of estimating the parameters of linear regression models by the least absolute deviations method is described. It is based on the descent through the nodal straight lines. This algorithm significantly outperforms other well-known methods of solving the problem and it can be effectively used in practice. The computational complexity of the descent algorithm through the nodal straight lines is assessed. © 2021 Author(s).
URI: http://hdl.handle.net/10995/103040
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85102728608
PURE ID: 21042933
740a9afd-5e57-4c12-a0c4-adeff667440b
ISSN: 0094243X
ISBN: 9780735440777
DOI: 10.1063/5.0041859
metadata.dc.description.sponsorship: The research was supported by a grant from the Russian Fund of Fundamental Research, project no. 20-41-660008.
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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