Package: MaxMC 0.1.2

Gabriel Rodriguez-Rondon

MaxMC: Maximized Monte Carlo

An implementation of the Monte Carlo techniques described in details by Dufour (2006) <doi:10.1016/j.jeconom.2005.06.007> and Dufour and Khalaf (2007) <doi:10.1002/9780470996249.ch24>. The two main features available are the Monte Carlo method with tie-breaker, mc(), for discrete statistics, and the Maximized Monte Carlo, mmc(), for statistics with nuisance parameters.

Authors:Julien Neves [aut], Jean-Marie Dufour [aut, ths], Gabriel Rodriguez-Rondon [cre]

MaxMC_0.1.2.tar.gz
MaxMC_0.1.2.zip(r-4.7-any)MaxMC_0.1.2.zip(r-4.6-any)MaxMC_0.1.2.zip(r-4.5-any)
MaxMC_0.1.2.tgz(r-4.6-any)MaxMC_0.1.2.tgz(r-4.5-any)
MaxMC_0.1.2.tar.gz(r-4.7-any)MaxMC_0.1.2.tar.gz(r-4.6-any)
MaxMC_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MaxMC/json (API)

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

Bug tracker:https://github.com/julienneves/maxmc/issues

On CRAN:

Conda:

2.70 score 277 downloads 3 exports 20 dependencies

Last updated from:05171d8731. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK118
source / vignettesOK167
linux-releaseOK105
macos-releaseOK147
macos-oldrelOK167
windows-develOK72
windows-releaseOK62
windows-oldrelOK91
wasm-releaseOK93

Exports:mcmmcpvalue

Dependencies:clicodetoolscrayonfarverforeachGAGenSAglueiteratorslabelinglifecycleNMOFpsoR6RColorBrewerRcppRcppArmadillorlangscalesviridisLite