Motivated by classification issues in marine studies, we propose a hidden semi-Markov model to segment toroidal time series according to a finite number of latent regimes. The time spent in a given regime and the chances of a regime switching event are separately modeled by a battery of regression models that depend on time-varying covariates.
Segmenting toroidal time series by nonhomogeneous hidden semi-Markov models / Francesco Lagona; Marco Mingione. - (2023), pp. 197-200.
Segmenting toroidal time series by nonhomogeneous hidden semi-Markov models
Marco Mingione
2023
Abstract
Motivated by classification issues in marine studies, we propose a hidden semi-Markov model to segment toroidal time series according to a finite number of latent regimes. The time spent in a given regime and the chances of a regime switching event are separately modeled by a battery of regression models that depend on time-varying covariates.
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