Clustering multivariate longitudinal observations: The contaminated Gaussian hidden Markov model
The Gaussian hidden Markov model (HMM) is widely considered for the analysis of heterogeneous continuous multivariate longitudinal data. To robustify this approach with respect to possible elliptical heavy-tailed departures from normality, due to the presence of outliers, spurious points, or noise (...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
2015-09-29.
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| Subjects: | |
| Online Access: | Get fulltext |