Copula-based hidden semi-Markov models for mixed support data
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ID: 320902
2026
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Abstract
Abstract Motivated by a classification problem in directional statistics, we extend the class of hidden semi-Markov models to a copula-based setting. The proposal segments a bivariate time series of mixed support data according to a finite number of latent classes, associated with copula-based densities, simultaneously estimating the distribution of the time spent by the system within each class. The flexibility of the proposed method is illustrated in the non-standard setting of a bivariate time series of mixed observations with a circular and linear support (wave height and direction).
| Reference Key |
openalex_W7168286552
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| Authors | Marco Mingione, Francesco Lagona |
| Journal | Journal of the Royal Statistical Society Series C (Applied Statistics) |
| Year | 2026 |
| DOI |
10.1093/jrsssc/qlag039
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| URL | |
| Keywords | Keywords not found |
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