Statistical analysis of multivariate binary time series based on a neural network model

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.

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Publication Details

Journal
Doklady of the National Academy of Sciences of Belarus
Published
2024-09-05
DOI
https://doi.org/10.29235/1561-8323-2024-68-4-271-281
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Statistical analysis of multivariate binary time series based on a neural network model

Yu. S. Kharin, S. A. Shibalko
Doklady of the National Academy of Sciences of Belarus
Neural Networks and Applications
article

Statistical analysis of multivariate binary time series based on a neural network model

Yu. S. Kharin, S. A. Shibalko
article en

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.

Doklady of the National Academy of Sciences of BelarusVol. 68(4)
Belarusian State University (BY)
Openalex Percentile: Top 87%
Neural Networks and Applications
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