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.
- Version0.2.6
- R versionR (≥ 3.5.0)
- LicenseGPL-3
- Needs compilation?No
- Last release09/07/2025
Team
Bouchra R. Nasri
MaintainerShow author detailsBruno N. Remillard
Show author detailsRolesAuthor, Copyright holderMamadou Yamar Thioub
Show author detailsRolesAuthor, Copyright holder
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Dependencies
- Depends2 packages
- Imports17 packages