abcrf: Approximate Bayesian Computation via Random Forests

Performs Approximate Bayesian Computation (ABC) model choice and parameter inference via random forests. Pudlo P., Marin J.-M., Estoup A., Cornuet J.-M., Gautier M. and Robert C. P. (2016) <doi:10.1093/bioinformatics/btv684>. Estoup A., Raynal L., Verdu P. and Marin J.-M. <http://journal-sfds.fr/article/view/709>. Raynal L., Marin J.-M., Pudlo P., Ribatet M., Robert C. P. and Estoup A. (2019) <doi:10.1093/bioinformatics/bty867>.

Version:	1.9
Depends:	R (≥ 3.1)
Imports:	readr, MASS, matrixStats, ranger, doParallel, parallel, foreach, stringr, Rcpp (≥ 0.11.2)
LinkingTo:	Rcpp, RcppArmadillo
Published:	2022-08-09
Author:	Jean-Michel Marin [aut, cre], Louis Raynal [aut], Pierre Pudlo [aut], Christian P. Robert [ctb], Arnaud Estoup [ctb]
Maintainer:	Jean-Michel Marin <jean-michel.marin at umontpellier.fr>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
In views:	Bayesian
CRAN checks:	abcrf results

Documentation:

Reference manual:

abcrf.pdf

Downloads:

Package source:	abcrf_1.9.tar.gz
Windows binaries:	r-devel: abcrf_1.9.zip, r-release: abcrf_1.9.zip, r-oldrel: abcrf_1.9.zip
macOS binaries:	r-release (arm64): abcrf_1.9.tgz, r-oldrel (arm64): abcrf_1.9.tgz, r-release (x86_64): abcrf_1.9.tgz, r-oldrel (x86_64): abcrf_1.9.tgz
Old sources:	abcrf archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=abcrf to link to this page.