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>. Raynal, L., Marin, J.-M., Pudlo, P., Ribatet, M., Robert, C.P. and Estoup, A. (2017) <arXiv:1605.05537>.

Version: 1.7.1
Depends: R (≥ 3.1)
Imports: readr, MASS, matrixStats, ranger, parallel, stringr, Rcpp (≥ 0.11.2)
LinkingTo: Rcpp, RcppArmadillo
Published: 2018-06-27
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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: abcrf results


Reference manual: abcrf.pdf
Package source: abcrf_1.7.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: abcrf_1.7.1.tgz, r-oldrel: abcrf_1.7.1.tgz
Old sources: abcrf archive


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