Damásio, BrunoNicolau, João2024-01-242024-01-242024-030960-0779PURE: 82237761PURE UUID: 411e856d-06b7-49fc-b36b-ebc62d4da7e1Scopus: 85183472738WOS: 001167025500001http://hdl.handle.net/10362/162726Damásio, 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.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.151243848engInhomogeneous Markov chainStructural breaksTime-varying probabilitiesStatistical and Nonlinear PhysicsMathematical PhysicsGeneral Physics and AstronomyApplied Mathematicsjournal article10.1016/j.chaos.2024.114478https://www.scopus.com/pages/publications/85183472738https://www.webofscience.com/wos/woscc/full-record/WOS:001167025500001