Package: boodist 1.0.0.9000

Stéphane Laurent

boodist: Some Distributions from the 'Boost' Library and More

Make some distributions from the 'C++' library 'Boost' available in 'R'. In addition, the normal-inverse Gaussian distribution and the generalized inverse Gaussian distribution are provided. The distributions are represented by 'R6' classes. The method to sample from the generalized inverse Gaussian distribution is the one given in "Random variate generation for the generalized inverse Gaussian distribution" Luc Devroye (2012) <doi:10.1007/s11222-012-9367-z>.

Authors:Stéphane Laurent [aut, cre]

boodist_1.0.0.9000.tar.gz
boodist_1.0.0.9000.zip(r-4.7)boodist_1.0.0.9000.zip(r-4.6)boodist_1.0.0.9000.zip(r-4.5)
boodist_1.0.0.9000.tgz(r-4.6-x86_64)boodist_1.0.0.9000.tgz(r-4.6-arm64)boodist_1.0.0.9000.tgz(r-4.5-x86_64)boodist_1.0.0.9000.tgz(r-4.5-arm64)
boodist_1.0.0.9000.tar.gz(r-4.7-arm64)boodist_1.0.0.9000.tar.gz(r-4.7-x86_64)boodist_1.0.0.9000.tar.gz(r-4.6-arm64)boodist_1.0.0.9000.tar.gz(r-4.6-x86_64)
boodist_1.0.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
boodist/json (API)

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

Bug tracker:https://github.com/stla/boodist/issues

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

On CRAN:

Conda:

boostdistributionsrcppcpp

3.04 score 22 scripts 357 downloads 11 exports 5 dependencies

Last updated from:e08e19ebd7. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK262
linux-devel-x86_64OK297
source / vignettesOK287
linux-release-arm64OK271
linux-release-x86_64OK257
macos-release-arm64OK167
macos-release-x86_64OK411
macos-oldrel-arm64OK190
macos-oldrel-x86_64OK378
windows-develOK262
windows-releaseOK209
windows-oldrelOK151
wasm-releaseOK208

Exports:BetafindChi2dffindChi2ncpGeneralizedInverseGaussianGumbelHyperexponentialInverseGammaInverseGaussianNormalInverseGaussianSkewNormalStudent

Dependencies:BHR6RcppRcppEigenRcppNumerical