Package: CHMM 0.1.1

CHMM: Coupled Hidden Markov Models

An exact and a variational inference for coupled Hidden Markov Models applied to the joint detection of copy number variations.

Authors:Xiaoqiang Wang [aut], Julie Aubert [aut, cre]

CHMM_0.1.1.tar.gz
CHMM_0.1.1.zip(r-4.7-x86_64)CHMM_0.1.1.zip(r-4.7-arm64)CHMM_0.1.1.zip(r-4.6-x86_64)CHMM_0.1.1.zip(r-4.6-arm64)CHMM_0.1.1.zip(r-4.5-x86_64)
CHMM_0.1.1.tgz(r-4.6-x86_64)CHMM_0.1.1.tgz(r-4.6-arm64)CHMM_0.1.1.tgz(r-4.5-x86_64)CHMM_0.1.1.tgz(r-4.5-arm64)
CHMM_0.1.1.tar.gz(r-4.7-arm64)CHMM_0.1.1.tar.gz(r-4.7-x86_64)CHMM_0.1.1.tar.gz(r-4.6-arm64)CHMM_0.1.1.tar.gz(r-4.6-x86_64)
CHMM_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CHMM/json (API)

# Install 'CHMM' in R:
install.packages('CHMM', repos = c('https://julieaubert.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/julieaubert/chmm/issues

Datasets:
  • toydata - Toy example - observations for 5 correlated samples.
  • toystatus - Toy example - status for 5 correlated samples.

On CRAN:

Conda:

3.92 score 7 stars 12 scripts 268 downloads 2 mentions 11 exports 1 dependencies

Last updated from:cf283a7e25. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK94
linux-devel-x86_64OK100
source / vignettesOK139
linux-release-arm64OK92
linux-release-x86_64OK95
macos-release-arm64OK86
macos-release-x86_64OK190
macos-oldrel-arm64OK63
macos-oldrel-x86_64OK155
windows-devel-arm64OK337
windows-devel-x86_64OK105
windows-release-arm64OK341
windows-release-x86_64OK76
windows-oldrel-x86_64OK71
wasm-releaseOK93

Exports:BackwardRCHMM_EMCHMM_VEMclustersegcoupledHMMExpGridForwardRinit.EMinit.VEMviterbi_algoWl

Dependencies:mclust