Package: SANple 0.2.0

Francesco Denti

SANple: Fitting Shared Atoms Nested Models via Markov Chains Monte Carlo

Estimate Bayesian nested mixture models via Markov Chain Monte Carlo methods. Specifically, the package implements the common atoms model (Denti et al., 2023), and hybrid finite-infinite models. All models use Gaussian mixtures with a normal-inverse-gamma prior distribution on the parameters. Additional functions are provided to help analyzing the results of the fitting procedure. References: Denti, Camerlenghi, Guindani, Mira (2023) <doi:10.1080/01621459.2021.1933499>, D’Angelo, Denti (2024) <doi:10.1214/24-BA1458>.

Authors:Francesco Denti [aut, cre], Laura D'Angelo [aut, cph]

SANple_0.2.0.tar.gz
SANple_0.2.0.zip(r-4.7-x86_64)SANple_0.2.0.zip(r-4.7-arm64)SANple_0.2.0.zip(r-4.6-x86_64)SANple_0.2.0.zip(r-4.6-arm64)
SANple_0.2.0.tar.gz(r-4.7-arm64)SANple_0.2.0.tar.gz(r-4.7-x86_64)SANple_0.2.0.tar.gz(r-4.6-arm64)SANple_0.2.0.tar.gz(r-4.6-x86_64)
SANple_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SANple/json (API)

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

Bug tracker:https://github.com/laura-dangelo/sanple/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cppopenmp

1.70 score 2 scripts 277 downloads 5 exports 14 dependencies

Last updated from:3a0c4d385d. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK134
linux-devel-x86_64OK131
source / vignettesOK272
linux-release-arm64OK114
linux-release-x86_64OK125
windows-devel-arm64OK214
windows-devel-x86_64OK175
windows-release-arm64OK225
windows-release-x86_64OK97
wasm-releaseOK151

Exports:estimate_clusterssample_CAMsample_fiSANsample_fSANtraceplot

Dependencies:clifarvergluelabelinglifecycleR6RColorBrewerRcppRcppArmadilloRcppProgressrlangsalsoscalesviridisLite