Non-homogeneous high-order Markov chains: models and their probabilistic-statistical analysis
https://doi.org/10.29235/1561-8323-2026-70-3-191-200
Abstract
The paper is devoted to the development of probabilistic and statistical analysis of non-homogeneous high-order Markov chains for cases in which the matrix of one-step transition probabilities is time-varying. Models for deterministically non-homogeneous and stochastically non-homogeneous high-order Markov chains are constructed. Probabilistic properties of these models are analyzed and some approaches to statistical estimation of the model parameters are proposed.
Supporting agencies: This research is partially financially supported by the project on GP “Convergence–2030”.
About the Author
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., 220030, Minsk
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