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CMCMC  

Contemporaneous Markov Chain Monte Carlo
View on CRAN: Click here


Download and install CMCMC package within the R console
Install from CRAN:
install.packages("CMCMC")

Install from Github:
library("remotes")
install_github("cran/CMCMC")

Install by package version:
library("remotes")
install_version("CMCMC", "0.0.1")



Attach the package and use:
library("CMCMC")
Maintained by
Ahmad ALQabandi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-23
Latest Update: 2026-07-23
Description:
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.
How to cite:
Ahmad ALQabandi (2026). CMCMC: Contemporaneous Markov Chain Monte Carlo. R package version 0.0.1, https://cran.r-project.org/web/packages/CMCMC. Accessed 04 Oct. 2026.
Previous versions and publish date:
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Complete documentation for CMCMC
Functions, R codes and Examples using the CMCMC R package
Full CMCMC package functions and examples
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