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'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

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

openblascpp

7.31 score 4 stars 17 packages 310 scripts 1.6k downloads 4 mentions 14 exports 28 dependencies

Last updated 3 years agofrom:c7bc2c7d2e. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 03 2024
R-4.5-linux-x86_64NOTEDec 03 2024

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

Dependencies:briocallrclicrayondescdiffobjdigestellipseevaluatefftwtoolsfsgluejsonlitelifecyclemagrittrpkgbuildpkgloadpraiseprocessxpsR6RcppRcppArmadillorlangrprojroottestthatwaldowithr

Using mcmcse

Rendered frommcmcse_vignette.Rnwusingknitr::knitron Dec 03 2024.

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