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Sibirskii Zhurnal Industrial'noi Matematiki, 2016, Volume 19, Number 4, Pages 51–60
DOI: https://doi.org/10.17377/sibjim.2016.19.406 (Mi sjim938) 		 
This article is cited in 3 scientific papers (total in 3 papers)

On the asymptotic optimality of orthoregressional estimates

A. A. Lomovab

a Sobolev Institute of Mathematics SB RAS, 4 Koptyug av., 630090 Novosibirsk
b Novosibirsk State University, 2 Pirogova str., 630090 Novosibirsk
Full-text PDF (241 kB) Citations (3)
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DOI: https://doi.org/10.17377/sibjim.2016.19.406
Abstract: It is shown that the orthoregressive (STLS) parameter estimates in simultaneous linear systems (including autonomous difference equations with matrix coefficients) converge to the maximum likelihood estimates and thus become asymptotically best in the limit case of large variances of random coordinates on the manifold of solutions to the system observed with additive random perturbations.
Keywords: linear autonomous difference equation, parameter identification, orthoregressive estimate, STLS estimate, asymptotic efficiency.
Funding agency Grant number
Russian Foundation for Basic Research 16-01-00592
Russian Academy of Sciences - Federal Agency for Scientific Organizations 0314-2015-0011
Received: 17.08.2015
English version:
Journal of Applied and Industrial Mathematics, 2016, Volume 10, Issue 4, Pages 511–519
DOI: https://doi.org/10.1134/S1990478916040074
Bibliographic databases:
Document Type: Article
UDC: 681.5.015
Language: Russian
Citation: A. A. Lomov, “On the asymptotic optimality of orthoregressional estimates”, Sib. Zh. Ind. Mat., 19:4 (2016), 51–60; J. Appl. Industr. Math., 10:4 (2016), 511–519
Citation in format AMSBIB
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    • This publication is cited in the following 3 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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    		Сибирский журнал индустриальной математики
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