Package: geommc 1.3.2

Vivekananda Roy

geommc: Geometric Markov Chain Sampling

Simulates from discrete and continuous target distributions using geometric Metropolis-Hastings (MH) algorithms. Users specify the target distribution by an R function that evaluates the log un-normalized pdf or pmf. The package also contains a function implementing a specific geometric MH algorithm for performing high-dimensional Bayesian variable selection.

Authors:Vivekananda Roy [aut, cre]

geommc_1.3.2.tar.gz
geommc_1.3.2.tar.gz(r-4.7-arm64)geommc_1.3.2.tar.gz(r-4.7-x86_64)geommc_1.3.2.tar.gz(r-4.6-arm64)geommc_1.3.2.tar.gz(r-4.6-x86_64)
geommc_1.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
geommc/json (API)

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

Bug tracker:https://github.com/vroys/geommc/issues

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

On CRAN:

Conda:

openblascppopenmp

2.60 score 3 scripts 488 downloads 3 exports 17 dependencies

Last updated from:9e4c7a72e9. Checks:4 WARNING, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64WARNING149
linux-devel-x86_64WARNING189
source / vignettesOK417
linux-release-arm64WARNING650
linux-release-x86_64WARNING149
wasm-releaseOK135

Exports:geomcgeomc.vslogp.vs

Dependencies:clicrayoncubaturegluehmslatticelifecycleMatrixnumDerivpkgconfigprettyunitsprogressR6RcppRcppArmadillorlangvctrs

Bayesian variable selection with geomc.vs

Vivekananda Roy

Rendered fromgeomc-vs.Rmdusingknitr::rmarkdownon Jun 08 2026.

Last update: 2026-02-27
Started: 2026-02-27

Geometric MCMC sampling with geomc

Vivekananda Roy

Rendered fromgeomc.Rmdusingknitr::rmarkdownon Jun 08 2026.

Last update: 2026-05-09
Started: 2026-02-27