Statistical analysis of multivariate binary time series based on a neural network model
https://doi.org/10.29235/1561-8323-2024-68-4-271-281
Abstract
This article is devoted to the statistical analysis of multivariate binary time series. For solving this problem a parsimonious neural network model of Markov’s ergodic chain of order s was determined. Consistent statistical estimators for model parameters and estimation algorithms of parameters and forecasting algorithms of future states of time series were developed. The results of computer experiments on simulated and real data are presented.
About the Authors
Yu. S. Kharin
Research Institute for Applied Problems of Mathematics and Informatics of the Belarusian State University
Belarus
Belarus
Kharin Yuriy S. – Academician, D. Sc. (Physics and Mathematics), Professor, Director
4, Nezavisimosti Ave., Minsk, 220030
S. A. Shibalko
Belarusian State University
Belarus
Belarus
Shibalko Siarhei A. – Student
4, Nezavisimosti Ave., Minsk, 220030
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