Goodness-of-Fit for Zero-Inflated Univariate Hidden Markov Models R package GenHMM1d version 0.2.6 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>. Software Depends: R (>= 3.5.0), doParallel, parallel, foreach Imports: ggplot2, stats, matrixcalc, reshape2, rmutil, VaRES, VGAM, EnvStats, GLDEX, GeneralizedHyperbolic, actuar, extraDistr, gamlss.dist, sgt, skewt, sn, ssdtools, stabledist Bouchra R. Nasri <bouchra.nasri@umontreal.ca> Comprehensive R Archive Network (CRAN) Bouchra R. Nasri [aut, cre, cph], Mamadou Yamar Thioub [aut, cph], Bruno N. Remillard [aut, cph] GPL-3 2025-09-07 application/tgz https://CRAN.R-project.org/package=GenHMM1d doi:10.32614/CRAN.package.GenHMM1d