Application of the Polynomial Maximization Method for Estimation Parameters in the Polynomial Regression with Non-Gaussian Advances in Intelligent Systems and Computing

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dc.contributor.authorZabolotnii, Serhii
dc.contributor.authorЗаболотній, Сергій Васильович
dc.contributor.authorTkachenko, Oleksandr
dc.contributor.authorТкаченко, Олександр Миколайович
dc.contributor.authorWarsza, Zygmunt Lech
dc.date.accessioned2025-11-27T12:22:34Z
dc.date.available2025-11-27T12:22:34Z
dc.date.issued2021
dc.description.abstractThis paper considers the application of the polynomial maximization method to find estimates of the parameters of polynomial regression. It is shown that this method can be effective for the case when the distribution of the random component of the regression models differs significantly from the Gaussian distribution. This approach is adaptive and is based on the analysis of higher-order statistics of regression residuals. Analytical expressions that allow finding estimates and analyzing their uncertainty are obtained. Cases of asymmetry and symmetry of the distribution of regression errors are considered. It is shown that the variance of estimates of the polynomial maximization method can be significantly less than the variance of the estimates of the least squares method, which is a special case. The increase in accuracy depends on the values of the cumulant coefficients of higher orders of random errors of the regression model. 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. Application of the Polynomial Maximization Method for Estimation Parameters in the Polynomial Regression with Non-Gaussian Advances in Intelligent Systems and Computing. Automation 2021: Recent Achievements in Automation, Robotics and Measurement Techniques. Springer Cham. [Електронне видання]. 2021. р. 415-420. DOI: https://doi.org/10.1007/978-3-030-74893-7_36 [Scopus]
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-030-74893-7_36
dc.identifier.urihttps://dr.csbc.edu.ua/handle/123456789/682
dc.publisherSpringer Nature
dc.subjectSOCIAL SCIENCES::Statistics, computer and systems science
dc.titleApplication of the Polynomial Maximization Method for Estimation Parameters in the Polynomial Regression with Non-Gaussian Advances in Intelligent Systems and Computing
dc.typeConference paper
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