Package: mcmcse 1.5-0

Dootika Vats

mcmcse: Monte Carlo Standard Errors for MCMC

Provides tools for computing Monte Carlo standard errors (MCSE) in Markov chain Monte Carlo (MCMC) settings. MCSE computation for expectation and quantile estimators is supported as well as multivariate estimations. The package also provides functions for computing effective sample size and for plotting Monte Carlo estimates versus sample size.

Authors:James M. Flegal <[email protected]>, John Hughes, Dootika Vats <[email protected]>, Ning Dai, Kushagra Gupta, and Uttiya Maji

mcmcse_1.5-0.tar.gz
mcmcse_1.5-0.tar.gz(r-4.5-noble)mcmcse_1.5-0.tar.gz(r-4.4-noble)
mcmcse_1.5-0.tgz(r-4.4-emscripten)mcmcse_1.5-0.tgz(r-4.3-emscripten)
mcmcse.pdf |mcmcse.html✨
mcmcse/json (API)

# Install 'mcmcse' in R:
install.packages('mcmcse', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

openblascpp

5.80 score 4 stars 17 packages 1.5k downloads 4 mentions 14 exports 28 dependencies

Last updated 4 years agofrom:c7bc2c7d2e. Checks:1 OK, 1 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 03 2025
R-4.5-linux-x86_64NOTEMar 03 2025

Exports:batchSizeBVN_GibbsconfRegionessestvssampis.mcmcsemcsemcse.initseqmcse.matmcse.multimcse.qmcse.q.matminESSmultiESS

Dependencies:briocallrclicrayondescdiffobjdigestellipseevaluatefftwtoolsfsgluejsonlitelifecyclemagrittrpkgbuildpkgloadpraiseprocessxpsR6RcppRcppArmadillorlangrprojroottestthatwaldowithr

Using mcmcse

Rendered frommcmcse_vignette.Rnwusingknitr::knitron Mar 03 2025.

Last update: 2021-09-09
Started: 2015-08-01