Inference, Goodness-of-Fit and Forecast for Univariate Gaussian Hidden Markov Models R package GaussianHMM1d version 1.1.2 Inference, goodness-of-fit test, and prediction densities and intervals for univariate Gaussian Hidden Markov Models (HMM). The goodness-of-fit 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 Chapter 10.2 of Remillard (2013) <doi:10.1201/b14285>. Software Depends: R (>= 3.5.0), doParallel, parallel, foreach, stats Bouchra R. Nasri <bouchra.nasri@umontreal.ca> Comprehensive R Archive Network (CRAN) Bouchra R. Nasri [aut, cre, cph], Bruno N Remillard [aut, ctb, cph] GPL (>= 2) 2025-02-05 application/tgz https://CRAN.R-project.org/package=GaussianHMM1d doi:10.32614/CRAN.package.GaussianHMM1d