Time inhomogeneous multivariate Markov chains

Damásio, Bruno; Nicolau, João

http://hdl.handle.net/10362/162726

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Autores

Damásio, Bruno

Nicolau, João

Resumo(s)

Markov chain models are used in several applications and different areas of study. A Markov chain model is usually assumed to be homogeneous in the sense that the transition probabilities are time-invariant. Yet, ignoring the inhomogeneous nature of a stochastic process by disregarding the presence of structural breaks can lead to misleading conclusions. Several methodologies are currently proposed for detecting structural breaks in a Markov chain. However, these methods have some limitations: namely they can only test directly for the presence of a single structural break. This paper proposes a new methodology for detecting and testing the presence of multiple structural breaks in a Markov chain occurring at unknown dates.

Descrição

Damásio, B., & Nicolau, J. (2024). Time inhomogeneous multivariate Markov chains: Detecting and testing multiple structural breaks occurring at unknown dates. Chaos, Solitons & Fractals, 180, 1-15. Article 114478. https://doi.org/10.1016/j.chaos.2024.114478 --- Bruno Damásio acknowledges the financial support provided by Fundação para a Ciência e a Tecnologia, Portugal (FCT) under the project UIDB/04152/2020 — Centro de Investigação em Gestão de Informação (MagIC). João Nicolau acknowledges the financial support provided by FCT under the project CEMAPRE/REM - UIDB/05069/2020.

Palavras-chave

Inhomogeneous Markov chain Structural breaks Time-varying probabilities Statistical and Nonlinear Physics Mathematical Physics General Physics and Astronomy Applied Mathematics