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-4.5)rgw_0.3.0.zip(r-4.4)rgw_0.3.0.zip(r-4.3)
rgw_0.3.0.tgz(r-4.4-any)rgw_0.3.0.tgz(r-4.3-any)
rgw_0.3.0.tar.gz(r-4.5-noble)rgw_0.3.0.tar.gz(r-4.4-noble)
rgw_0.3.0.tgz(r-4.4-emscripten)rgw_0.3.0.tgz(r-4.3-emscripten)
rgw.pdf |rgw.html✨
rgw/json (API)

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

Peer review:

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

On CRAN:

markov-chain-monte-carlostatistics

3.00 score 2 stars 2 scripts 152 downloads 2 exports 0 dependencies

Last updated 1 years agofrom:7cb69aa12e. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winOKNov 17 2024
R-4.5-linuxOKNov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winOKNov 17 2024
R-4.3-macOKNov 17 2024

Exports:GoodmanWeareGoodmanWeare.rem

Dependencies: