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GenHMM1d: Goodness-of-Fit for Zero-Inflated Univariate Hidden Markov Models
Inference, goodness-of-fit tests, and predictions for continuous and discrete univariate Hidden Markov Models (HMM), including zero-inflated distributions. The goodness-of-fit test is based on a Cramer-von Mises statistic and uses parametric bootstrap to estimate the p-value. The description of the methodology is taken from Nasri et al (2020) <doi:10.1029/2019WR025122>.
Getting started
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Package details |
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| Author | Bouchra R. Nasri [aut, cre, cph], Mamadou Yamar Thioub [aut, cph], Bruno N. Remillard [aut, cph] |
| Maintainer | Bouchra R. Nasri <bouchra.nasri@umontreal.ca> |
| License | GPL-3 |
| Version | 0.2.6 |
| Package repository | View on CRAN |
| Installation |
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