Application of the Polynomial Maximization Method for Estimation Parameters of Autoregressive Models with Asymmetric Innovations
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Nature
Abstract
This paper considers the application of the Polynomial Maximization Method to find estimates of the parameters of autoregressive model with non-Gaussian innovation. This approach is adaptive and is based on the analysis of higher-order statistics. Analytical expressions that allow finding estimates and analyzing their uncertainty are obtained. Case of asymmetry of the distribution of autoregressive innovations is 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 linear approach (based on Yule-Walker equation or Ordinary Least Squares). The increase in accuracy depends on the values of the cumulant coefficients of higher orders of innovation residuals. The results of statistical modeling by the Monte Carlo method confirm the effectiveness of the proposed approach.
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Keywords
SOCIAL SCIENCES::Statistics, computer and systems science::Informatics, computer and systems science, MATHEMATICS::Applied mathematics
Citation
Zabolotnii S. V., Tkachenko O. M., Warsza Z. L. Application of the Polynomial Maximization Method for Estimation Parameters of Autoregressive Models with Asymmetric Innovations. Automation 2022: New Solutions and Technologies for Automation, Robotics and Measurement Techniques. [Електронне видання]. 2022. pp. 380-390. DOI: 10.1007/978-3-031-03502-9_37