Vestnik Sankt-Peterburgskogo Universiteta. Seriya 10. Prikladnaya Matematika. Informatika. Protsessy Upravleniya
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Vestnik Sankt-Peterburgskogo Universiteta. Seriya 10. Prikladnaya Matematika. Informatika. Protsessy Upravleniya, 2023, Volume 19, Issue 4, Pages 484–496
DOI: https://doi.org/10.21638/11701/spbu10.2023.405
(Mi vspui597)
 

Applied mathematics

Algorithm of variance estimation in weighted least squares method

A. V. Prasolov, N. G. Ivanov, N. V. Smirnov

St. Petersburg State University, 7–9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation
References:
Abstract: The representation of a time series model as a piecewise-stationary process is provided, wherein it is regarded as a collection of successive stationary intervals. An algorithm has been developed for identifying the domain containing the trend within this model. It is recognized that applying the least squares method directly for trend determination is not commonly employed in statistical analysis and econometric software packages. Typically, the weighted least squares method is utilized to ideally eliminate non-stationarity. The authors presents an algorithm for estimating the weight coefficients for this method through piecewise-stationary modeling. The algorithm has been tested on time series of various natures.
Keywords: time series, piecewise-stationary process, weighted least squares method.
Funding agency Grant number
Russian Foundation for Basic Research 20-31-90063
This work was supported by the Russian Foundation for Basic Research (project N 20-31-90063).
Received: August 25, 2023
Accepted: October 12, 2023
Document Type: Article
UDC: 519.246.8
MSC: 37M10
Language: Russian
Citation: A. V. Prasolov, N. G. Ivanov, N. V. Smirnov, “Algorithm of variance estimation in weighted least squares method”, Vestnik S.-Petersburg Univ. Ser. 10. Prikl. Mat. Inform. Prots. Upr., 19:4 (2023), 484–496
Citation in format AMSBIB
\Bibitem{PraIvaSmi23}
\by A.~V.~Prasolov, N.~G.~Ivanov, N.~V.~Smirnov
\paper Algorithm of variance estimation in weighted least squares method
\jour Vestnik S.-Petersburg Univ. Ser. 10. Prikl. Mat. Inform. Prots. Upr.
\yr 2023
\vol 19
\issue 4
\pages 484--496
\mathnet{http://mi.mathnet.ru/vspui597}
\crossref{https://doi.org/10.21638/11701/spbu10.2023.405}
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