Package: DBHC 0.0.5

Gabriel Budel

DBHC: Sequence Clustering with Discrete-Output HMMs

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.

Authors:Gabriel Budel [aut, cre], Flavius Frasincar [aut]

DBHC_0.0.5.tar.gz
DBHC_0.0.5.zip(r-4.7-any)DBHC_0.0.5.zip(r-4.6-any)DBHC_0.0.5.zip(r-4.5-any)
DBHC_0.0.5.tgz(r-4.6-any)DBHC_0.0.5.tgz(r-4.5-any)
DBHC_0.0.5.tar.gz(r-4.7-any)DBHC_0.0.5.tar.gz(r-4.6-any)
DBHC_0.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
DBHC/json (API)

# Install 'DBHC' in R:

install.packages('DBHC', repos = c('https://gabybudel.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gabybudel/dbhc/issues

On CRAN:

4.00 score 1 stars 1 scripts 337 downloads 13 exports 91 dependencies

Last updated from:97c9531502. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	182
source / vignettes	OK	336
linux-release	OK	180
macos-release	OK	156
macos-oldrel	OK	194
windows-devel	OK	123
windows-release	OK	108
windows-oldrel	OK	109
wasm-release	OK	105

Exports:assign.clusters cluster.bic count.parameters emission.heatmap hmm.clust model.ll partition.bic select.seeds seq2hmm.ll size.search smooth.hmm smooth.probabilities transition.heatmap

Dependencies:backports bit bit64 boot checkmate cli clipr cluster codetools collapse colorspace commonmark cpp11 crayon curl data.table digest dplyr farver forcats future future.apply generics ggh4x ggplot2 ggrepel ggseqplot ggtext globals glue gridBase gridtext gtable haven hms igraph isoband jpeg labeling lattice lhs lifecycle listenv litedown magrittr markdown MASS Matrix mgcv nlme nloptr numDeriv parallelly patchwork permute pillar pkgconfig plyr png prettyunits progress progressr purrr R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppHungarian Rdpack readr reshape2 rlang S7 scales seqHMM stringi stringr tibble tidyr tidyselect TraMineR tzdb utf8 vctrs vegan viridisLite vroom withr xfun xml2

Clustering school-to-work trajectories with DBHC

Rendered fromschool-to-work.Rmdusingknitr::rmarkdown

Last update: 2026-08-07
Started: 2026-08-07

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Cluster Assignment	assign.clusters
HMM BIC	cluster.bic
Count HMM Parameters	count.parameters
Heatmap Emission Probabilities	emission.heatmap
DBHC Algorithm	hmm.clust
Get HMM Log Likelihood	model.ll
Partition BIC	partition.bic
Seed Selection Procedure	select.seeds
Sequence-to-HMM Likelihood	seq2hmm.ll
Size Search Algorithm	size.search
Smooth HMM Parameters	smooth.hmm
Smooth Probabilities	smooth.probabilities
Heatmap Transition Probabilities	transition.heatmap