Package: CMCMC 0.0.1

Ahmad ALQabandi

CMCMC: Contemporaneous Markov Chain Monte Carlo

Implements contemporaneous Markov chain Monte Carlo (CMCMC) and interchain adaptive Markov chain Monte Carlo (INCA) samplers of Craiu, Rosenthal and Yang (2009) <doi:10.1198/jasa.2009.tm08393> for targets known up to a normalising constant. The samplers run multiple Metropolis chains in parallel and update proposal covariance estimates using contemporaneous particle groups. Built-in target kernels include multivariate normal, logistic regression, Poisson, Gaussian, Gamma, and hierarchical models, with support for user-provided target kernels. The formula interface glm_cmcmc() fits supported generalized linear models using the built-in kernels. 'CUDA' is used when available, and an 'OpenMP'-enabled CPU backend is available on systems without a 'CUDA' compiler.

Authors:Ahmad ALQabandi [cre, aut, cph], Louis Aslett [aut, ths, cph], Murray Pollock [aut], Gareth Roberts [aut]

CMCMC_0.0.1.tar.gz
CMCMC_0.0.1.zip(r-4.7-x86_64)CMCMC_0.0.1.zip(r-4.7-arm64)
CMCMC_0.0.1.tar.gz(r-4.7-arm64)CMCMC_0.0.1.tar.gz(r-4.7-x86_64)CMCMC_0.0.1.tar.gz(r-4.6-arm64)CMCMC_0.0.1.tar.gz(r-4.6-x86_64)
CMCMC_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
CMCMC/json (API)

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

On CRAN:

Conda:

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

3.00 score 10 exports 0 dependencies

Last updated from:09fd0e4cac. Checks:8 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK241
linux-devel-x86_64OK212
source / vignettesOK297
linux-release-arm64OK259
linux-release-x86_64OK235
windows-devel-arm64OK213
windows-devel-x86_64OK112
wasm-releaseOK136

Exports:cmcmccmcmc_autotunecmcmc_autotune_clearcmcmc_autotune_listcmcmc_clear_kernel_cachecmcmcoptglm_cmcmcincaload_target_kernelload_target_kernel_cpu

Dependencies:

CMCMC Example Workflows
What Is CMCMC? | Quick Start | Backend Selection | Step Mode, Batch Mode, and Launch Tuning | Common Output Layout | Multivariate Normal | Hierarchical Beta-Binomial Rat Tumor Rates | User Kernel Interface | Model | CUDA and CPU Kernels | Running the Sampler | Posterior Checks | [E(\omega_j \mid y_j,n_j,\alpha,\beta) | References
Rendered fromcmcmc-examples.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23

GLM CMCMC
Overview | Binomial | Poisson | Gaussian | Gamma | Output
Rendered fromglm-cmcmc.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23