Polynomial Maximization Method for Estimation Parameters of Asymmetric Non-Gaussian Moving Average Models

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dc.contributor.authorZabolotnii, Serhii
dc.contributor.authorЗаболотній, Сергій Васильович
dc.contributor.authorTkachenko, Oleksandr
dc.contributor.authorWarsza, Zygmunt Lech
dc.date.accessioned2025-11-20T12:29:40Z
dc.date.available2025-11-20T12:29:40Z
dc.date.issued2023
dc.description.abstractThis paper considers the application of the Polynomial Maximization Method to find estimates of the parameters Non-Gaussian Moving Average model. This approach is adaptive and is based on the analysis of higher-order statistics. Case of asymmetry of the distribution of Moving Average processes is considered. It is shown that the asymptotic variance of estimates of the Polynomial Maximization Method (2nd order) analytical expressions that allow finding estimates and analyzing their uncertainty are obtained. This approach can be significantly less than the variance of the classic estimates based on minimize Conditional Sum of Squares or Maximum Likelihood (in Gaussian case). The increase in accuracy depends on the values of the coefficient’s asymmetry and kurtosis of residuals. The results of statistical modeling by the Monte Carlo Method confirm the effectiveness of the proposed approach.
dc.identifier.citationZabolotnii S. V., Tkachenko O. M., Warsza Z. L. Polynomial Maximization Method for Estimation Parameters of Asymmetric Non-Gaussian Moving Average Models. Key Challenges in Automation, Robotics and Measurement Techniques. AUTOMATION 2023. Lecture Notes in Networks and Systems. 2023. № 630. рр. 223-231. DOI: https://doi.org/10.1007/978-3-031-25844-2_21 [Scopus]
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-031-25844-2_21
dc.identifier.urihttps://dr.csbc.edu.ua/handle/123456789/650
dc.publisherSpringer Nature
dc.subjectSOCIAL SCIENCES::Statistics, computer and systems science::Informatics, computer and systems science
dc.subjectMATHEMATICS::Applied mathematics
dc.titlePolynomial Maximization Method for Estimation Parameters of Asymmetric Non-Gaussian Moving Average Models
dc.typeConference paper
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