Sequence Clustering with Discrete-Output HMMs R package DBHC version 0.0.3 Provides an implementation of a mixture of hidden Markov models (HMMs) for discrete sequence data in the Discrete Bayesian HMM Clustering (DBHC) algorithm. The DBHC algorithm is an HMM Clustering algorithm that finds a mixture of discrete-output HMMs while using heuristics based on Bayesian Information Criterion (BIC) to search for the optimal number of HMM states and the optimal number of clusters. Software Imports: seqHMM (>= 1.0.8), TraMineR (>= 2.0-7), reshape2 (>= 1.2.1), ggplot2 (>= 2.2.1), methods (>= 4.2.2) Suggests: testthat (>= 3.0.0) Gabriel Budel <gabysp_budel@hotmail.com> Comprehensive R Archive Network (CRAN) Gabriel Budel [aut, cre], Flavius Frasincar [aut] GPL (>= 3) 2022-12-22 application/tgz https://CRAN.R-project.org/package=DBHC doi:10.32614/CRAN.package.DBHC