Package: rgw 0.3.0

rgw: Goodman-Weare Affine-Invariant Sampling

Implementation of the affine-invariant method of Goodman & Weare (2010) <doi:10.2140/camcos.2010.5.65>, a method of producing Monte-Carlo samples from a target distribution.

Authors:Adam Mantz

rgw_0.3.0.tar.gz
rgw_0.3.0.zip(r-4.7-any)rgw_0.3.0.zip(r-4.6-any)rgw_0.3.0.zip(r-4.5-any)
rgw_0.3.0.tgz(r-4.6-any)rgw_0.3.0.tgz(r-4.5-any)
rgw_0.3.0.tar.gz(r-4.7-any)rgw_0.3.0.tar.gz(r-4.6-any)
rgw_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rgw/json (API)

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

Bug tracker:https://github.com/abmantz/rgw/issues

On CRAN:

Conda:

markov-chain-monte-carlostatistics

3.00 score 2 stars 2 scripts 187 downloads 2 exports 0 dependencies

Last updated from:7cb69aa12e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK85
source / vignettesOK168
linux-releaseOK89
macos-releaseOK141
macos-oldrelOK170
windows-develOK62
windows-releaseOK54
windows-oldrelOK52
wasm-releaseOK73

Exports:GoodmanWeareGoodmanWeare.rem

Dependencies: