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)DPCD_0.0.1.zip(r-4.6)DPCD_0.0.1.zip(r-4.5)
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 165 downloads 9 exports 52 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK146
source / vignettesOK218
linux-release-x86_64OK172
macos-release-arm64OK114
macos-oldrel-arm64OK136
windows-develOK111
windows-releaseOK100
windows-oldrelOK105
wasm-releaseOK116

Exports:bs_scoreextract_clustersmakeDiagonalSigmamakeSphericalSigmaplot_objectspost_predictiveprior_predictiveprocrustesrun_dpcd

Dependencies:abindbackportsbayesplotcheckmatecliclustercodacpp11distributionaldplyrfarvergenericsggplot2ggridgesgluegtableigraphisobandlabelinglatticelifecyclelpSolvemagrittrMatrixmatrixStatsmcclustnimblenumDerivpillarpkgconfigplyrposteriorpracmapurrrR6RColorBrewerRcppreshape2rlangS7scalesstringistringrtensorAtibbletidyrtidyselecttruncnormutf8vctrsviridisLitewithr