mcmcensemble: Ensemble Sampler for Affine-Invariant MCMC

Provides ensemble samplers for affine-invariant Monte Carlo Markov Chain, which allow a faster convergence for badly scaled estimation problems. Two samplers are proposed: the 'differential.evolution' sampler from ter Braak and Vrugt (2008) <doi:10.1007/s11222-008-9104-9> and the 'stretch' sampler from Goodman and Weare (2010) <doi:10.2140/camcos.2010.5.65>.

Version: 3.0.0
Depends: R (≥ 3.5)
Imports: future.apply, progressr
Suggests: bayesplot, coda, mockery, testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2021-04-28
Author: Hugo Gruson ORCID iD [cre, aut, cph], Sanda Dejanic [aut, cph], Andreas Scheidegger ORCID iD [aut, cph]
Maintainer: Hugo Gruson <hugo.gruson+R at normalesup.org>
BugReports: https://github.com/Bisaloo/mcmcensemble/issues
License: GPL-2
URL: https://github.com/Bisaloo/mcmcensemble, https://bisaloo.github.io/mcmcensemble/
NeedsCompilation: no
Materials: README NEWS
In views: Bayesian
CRAN checks: mcmcensemble results

Documentation:

Reference manual: mcmcensemble.pdf
Vignettes: Interaction of mcmcensemble with other packages for MCMC diagnostic and plotting
Frequently Asked Questions

Downloads:

Package source: mcmcensemble_3.0.0.tar.gz
Windows binaries: r-devel: mcmcensemble_3.0.0.zip, r-release: mcmcensemble_3.0.0.zip, r-oldrel: mcmcensemble_3.0.0.zip
macOS binaries: r-release (arm64): mcmcensemble_3.0.0.tgz, r-oldrel (arm64): mcmcensemble_3.0.0.tgz, r-release (x86_64): mcmcensemble_3.0.0.tgz
Old sources: mcmcensemble archive

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