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 |
DOI: |
10.32614/CRAN.package.abcrf |
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:
Downloads:
Reverse dependencies:
Linking:
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