Package: DPCD 0.0.1

DPCD: Dirichlet Process Clustering with Dissimilarities

A Bayesian hierarchical model for clustering dissimilarity data using the Dirichlet process. The latent configuration of objects and the number of clusters are automatically inferred during the fitting process. The package supports multiple models which are available to detect clusters of various shapes and sizes using different covariance structures. Additional functions are included to ensure adequate model fits through prior and posterior predictive checks.

Authors:Sam Morrissette [cph, aut, cre]

DPCD_0.0.1.tar.gz
DPCD_0.0.1.zip(r-4.7-any)DPCD_0.0.1.zip(r-4.6-any)DPCD_0.0.1.zip(r-4.5-any)
DPCD_0.0.1.tgz(r-4.6-any)DPCD_0.0.1.tgz(r-4.5-any)
DPCD_0.0.1.tar.gz(r-4.7-any)DPCD_0.0.1.tar.gz(r-4.6-any)
DPCD_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
DPCD/json (API)

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

Bug tracker:https://github.com/sammorrissette/dpcd/issues

Datasets:

On CRAN:

Conda:

3.18 score 2 scripts 219 downloads 9 exports 54 dependencies

Last updated from:95791e2c55. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK204
source / vignettesOK193
linux-releaseOK209
macos-releaseOK176
macos-oldrelOK196
windows-develOK99
windows-releaseOK107
windows-oldrelOK105
wasm-releaseOK139

Exports:bs_scoreextract_clustersmakeDiagonalSigmamakeSphericalSigmaplot_objectspost_predictiveprior_predictiveprocrustesrun_dpcd

Dependencies:abindbackportsbayesplotcheckmatecliclustercodacpp11distributionaldplyrfarvergenericsggdistggplot2ggridgesgluegtableigraphisobandlabelinglatticelifecyclelpSolvemagrittrMatrixmatrixStatsmcclustnimblenumDerivpillarpkgconfigplyrposteriorpracmapurrrquadprogR6RColorBrewerRcppreshape2rlangS7scalesstringistringrtensorAtibbletidyrtidyselecttruncnormutf8vctrsviridisLitewithr