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EasyABC: Efficient Approximate Bayesian Computation Sampling Schemes

Enables launching a series of simulations of a computer code from the R session, and to retrieve the simulation outputs in an appropriate format for post-processing treatments. Five sequential sampling schemes and three coupled-to-MCMC schemes are implemented.

Version:1.5.2
Depends:R (≥ 2.14.0),abc
Imports:pls,mnormt,MASS, parallel,lhs,tensorA
Published:2023-01-05
DOI:10.32614/CRAN.package.EasyABC
Author:Franck Jabot, Thierry Faure, Nicolas Dumoulin, Carlo Albert.
Maintainer:Nicolas Dumoulin <nicolas.dumoulin at inrae.fr>
License:GPL-3
URL:http://easyabc.r-forge.r-project.org/
NeedsCompilation:no
Materials:ChangeLog
CRAN checks:EasyABC results

Documentation:

Reference manual:EasyABC.html ,EasyABC.pdf

Downloads:

Package source: EasyABC_1.5.2.tar.gz
Windows binaries: r-devel:EasyABC_1.5.2.zip, r-release:EasyABC_1.5.2.zip, r-oldrel:EasyABC_1.5.2.zip
macOS binaries: r-release (arm64):EasyABC_1.5.2.tgz, r-oldrel (arm64):EasyABC_1.5.2.tgz, r-release (x86_64):EasyABC_1.5.2.tgz, r-oldrel (x86_64):EasyABC_1.5.2.tgz
Old sources: EasyABC archive

Reverse dependencies:

Reverse imports:nlrx

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=EasyABCto link to this page.


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