Abstract:
Self-consistent stationary level of non-stationary time series is investigated. The various purposes of practical use of this statistics are discussed. The main problem is an evaluation of significance level of any sample statistics. Unlike the classical problem of stationary test of two samples, in the case under consideration one should construct an indicator to predict the change in the non-stationary regime. For example, we consider special predictor of an attack of epilepsy.
Keywords:
stationary point, significance level, disorder indicator, electroencephalogram, epilepsy attack.
Bibliographic databases:
Document Type:
Preprint
Language: Russian
Citation:
A. A. Kislitsyn, A. B. Kozlova, M. B. Korsakova, E. L. Masherov, Yu. N. Orlov, “Stationary point of significance level for non-stationary distribution functions”, Keldysh Institute preprints, 2018, 113, 20 pp.
\Bibitem{KisKozKor18}
\by A.~A.~Kislitsyn, A.~B.~Kozlova, M.~B.~Korsakova, E.~L.~Masherov, Yu.~N.~Orlov
\paper Stationary point of significance level for non-stationary distribution functions
\jour Keldysh Institute preprints
\yr 2018
\papernumber 113
\totalpages 20
\mathnet{http://mi.mathnet.ru/ipmp2472}
\crossref{https://doi.org/10.20948/prepr-2018-113}
\elib{https://elibrary.ru/item.asp?id=35042007}
Linking options:
https://www.mathnet.ru/eng/ipmp2472
https://www.mathnet.ru/eng/ipmp/y2018/p113
This publication is cited in the following 1 articles:
A. A. Kislitsyn, “Programmnyi kompleks dlya analiza statistiki soglasovannogo urovnya statsionarnosti vremennykh ryadov”, Preprinty IPM im. M. V. Keldysha, 2020, 026, 22 pp.
Citation in format AMSBIB
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