Package: CDGHMM 0.1.5

CDGHMM: Hidden Markov Models for Multivariate Panel Data

Estimates hidden Markov models from the family of Cholesky-decomposed Gaussian hidden Markov models (CDGHMM) under various missingness schemes. This family improves upon estimation of traditional Gaussian HMMs by introducing parsimony, as well as, controlling for dropped out observations and non-random missingness. See Neal, Sochaniwsky and McNicholas (2024) <doi:10.1007/s11222-024-10462-0>.

Authors:Mackenzie R. Neal [aut, cre], Alexa A. Sochaniwsky [aut], Paul D. McNicholas [aut]

CDGHMM_0.1.5.tar.gz
CDGHMM_0.1.5.zip(r-4.7-any)CDGHMM_0.1.5.zip(r-4.6-any)CDGHMM_0.1.5.zip(r-4.5-any)
CDGHMM_0.1.5.tgz(r-4.6-any)CDGHMM_0.1.5.tgz(r-4.5-any)
CDGHMM_0.1.5.tar.gz(r-4.7-any)CDGHMM_0.1.5.tar.gz(r-4.6-any)
CDGHMM_0.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CDGHMM/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.30 score 1 stars 388 downloads 1 exports 4 dependencies

Last updated from:2ca44b6226. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK94
source / vignettesOK135
linux-releaseOK92
macos-releaseOK194
macos-oldrelOK155
windows-develOK48
windows-releaseOK61
windows-oldrelOK65
wasm-releaseOK75

Exports:cdghmm

Dependencies:latticeMASSMatrixmvtnorm