Abstract:
To estimate the unknown autoregression parameter in the case when noise has an infinite dispersion, the weighted estimate by the least-squares method is suggested. The limit distribution of the error of estimation is obtained. It is shown that the weighted estimate is asymptotically more exact in comparison with the common estimate by the least-squares method.
Presented by the member of Editorial Board:A. V. Nazin
Citation:
A. S. Markov, “Estimation of the autoregression parameter with infinite dispersion of noise”, Avtomat. i Telemekh., 2009, no. 1, 104–118; Autom. Remote Control, 70:1 (2009), 92–106
\Bibitem{Mar09}
\by A.~S.~Markov
\paper Estimation of the autoregression parameter with infinite dispersion of noise
\jour Avtomat. i Telemekh.
\yr 2009
\issue 1
\pages 104--118
\mathnet{http://mi.mathnet.ru/at11}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=2510675}
\zmath{https://zbmath.org/?q=an:1163.93393}
\transl
\jour Autom. Remote Control
\yr 2009
\vol 70
\issue 1
\pages 92--106
\crossref{https://doi.org/10.1134/S000511790901007X}
\isi{https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=Publons&SrcAuth=Publons_CEL&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=000263843600007}
\scopus{https://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-59849092574}
Linking options:
https://www.mathnet.ru/eng/at11
https://www.mathnet.ru/eng/at/y2009/i1/p104
This publication is cited in the following 3 articles:
A. E. Barysheva, A. S. Markov, A. A. Mitcel, “VAR assessment under nongaussian distribution of returns”, Rossijskij tehnologičeskij žurnal, 8:2 (2020), 67
Aliev T.A. Musaeva N.F. Suleymanova M.T., “Algorithms For Indicating the Beginning of Accidents Based on the Estimate of the Density Distribution Function of the Noise of Technological Parameters”, Autom. Control Comp. Sci., 52:3 (2018), 231–242
Bartlett A., McCormick W.P., “Estimation for Non-Negative Time Series with Heavy-Tail Innovations”, J. Time Ser. Anal., 34:1 (2013), 96–115