Application of the Polynomial Maximization Method for Estimating Nonlinear Regression Parameters with Non-Gaussian Asymmetric Errors

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dc.contributor.authorЗаболотній, Сергій Васильович
dc.contributor.authorZabolotnii, Serhii
dc.contributor.authorTkachenko, Oleksandr
dc.contributor.authorNowakowski, Waldemar
dc.contributor.authorWarsza, Zygmunt Lech
dc.date.accessioned2025-11-11T09:07:37Z
dc.date.available2025-11-11T09:07:37Z
dc.date.issued2024
dc.description.abstractIn the article, an alternative approach to estimating parameters in nonlinear regression models under asymmetric error distributions is examined. A novel approach for adaptive estimation is proposed, which is based on the use of second-order polynomial functions. This enables a straightforward implementation to account for deviations from Gaussian idealization in the form of moments up to the fourth order. It is demonstrated that the overall problem can algorithmically be reduced to the numerical solution of a system of nonlinear stochastic equations. Analytical expressions are obtained, which facilitate the estimation of parameters and the analysis of their asymptotic variance. Statistical modeling using the Monte Carlo method was conducted, and the results indicate that the accuracy of PMM2 estimates is comparable to SLS estimates and significantly so exceeds the accuracy of OLS estimates.
dc.identifier.citationZabolotnii S., Tkachenko O., Nowakowski W., Warsza Z.L. Application of the Polynomial Maximization Method for Estimating Nonlinear Regression Parameters with Non-Gaussian Asymmetric Errors. Conference on Automation 2024: Advances in Automation, Robotics and Measurement Techniques. 2024. рр. 342-356. DOI: https://doi.org/10.1007/978-3-031-78266-4_30 [Scopus]
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-031-78266-4_30
dc.identifier.urihttps://dr.csbc.edu.ua/handle/123456789/594
dc.publisherSpringer Nature
dc.subjectSOCIAL SCIENCES::Statistics, computer and systems science::Informatics, computer and systems science::Informatics
dc.subjectSOCIAL SCIENCES::Statistics, computer and systems science::Informatics, computer and systems science
dc.subjectSOCIAL SCIENCES::Statistics, computer and systems science::Informatics, computer and systems science::Informatics and systems science
dc.subjectTECHNOLOGY::Information technology
dc.subjectSOCIAL SCIENCES::Statistics, computer and systems science::Informatics, computer and systems science::Information processing
dc.subjectTECHNOLOGY::Information technology::Other information technology
dc.subjectSOCIAL SCIENCES::Statistics, computer and systems science::Informatics, computer and systems science::Computer and systems science
dc.subjectTECHNOLOGY::Information technology::Computer science
dc.subjectMATHEMATICS
dc.titleApplication of the Polynomial Maximization Method for Estimating Nonlinear Regression Parameters with Non-Gaussian Asymmetric Errors
dc.typeConference paper
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