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Preprints of the Keldysh Institute of Applied Mathematics, 2016, 007, 20 pp. (Mi ipmp2083)  
This article is cited in 2 scientific papers (total in 2 papers)

The basis patterns method for non-stationary time-series analysis

E. P. Kirina-Lilinskaya, Yu. N. Orlov, S. L. Fedorov
Full-text PDF (1163 kB) Citations (2)
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Abstract: The definitions of approximate expansion of empirical distribution function density over special basis patterns are proposed for non-stationary time series. The method of statistical recognition of the local state in terms of distribution function is formulated. The statistics of trend prediction is constructed.
Keywords: non-stationary time series, basis patterns, self-consistent stationary level, pattern recognition.
Funding agency Grant number
Russian Foundation for Basic Research 16-01-00342
Document Type: Preprint
Language: Russian
Citation: E. P. Kirina-Lilinskaya, Yu. N. Orlov, S. L. Fedorov, “The basis patterns method for non-stationary time-series analysis”, Keldysh Institute preprints, 2016, 007, 20 pp.
Citation in format AMSBIB
\Bibitem{KirOrlFed16}
\by E.~P.~Kirina-Lilinskaya, Yu.~N.~Orlov, S.~L.~Fedorov
\paper The basis patterns method for non-stationary time-series analysis
\jour Keldysh Institute preprints
\yr 2016
\papernumber 007
\totalpages 20
\mathnet{http://mi.mathnet.ru/ipmp2083}
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  • https://www.mathnet.ru/eng/ipmp/y2016/p7
    • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Препринты Института прикладной математики им. М. В. Келдыша РАН
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