The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

EMC2: Bayesian Hierarchical Analysis of Cognitive Models of Choice

Fit Bayesian (hierarchical) cognitive models using a linear modeling language interface using particle metropolis Markov chain Monte Carlo sampling with Gibbs steps. The diffusion decision model (DDM), linear ballistic accumulator model (LBA), racing diffusion model (RDM), and the lognormal race model (LNR) are supported. Additionally, users can specify their own likelihood function and/or choose for non-hierarchical estimation, as well as for a diagonal, blocked or full multivariate normal group-level distribution to test individual differences. Prior specification is facilitated through methods that visualize the (implied) prior. A wide range of plotting functions assist in assessing model convergence and posterior inference. Models can be easily evaluated using functions that plot posterior predictions or using relative model comparison metrics such as information criteria or Bayes factors. References: Stevenson et al. (2024) <doi:10.31234/osf.io/2e4dq>.

Version: 2.1.0
Depends: R (≥ 3.5.0)
Imports: abind, coda, corpcor, graphics, grDevices, magic, MASS, matrixcalc, methods, msm, mvtnorm, parallel, stats, Matrix, Rcpp, Brobdingnag, corrplot, colorspace, psych, utils, lpSolve, WienR
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0), vdiffr, knitr, rmarkdown
Published: 2024-10-14
DOI: 10.32614/CRAN.package.EMC2
Author: Niek Stevenson ORCID iD [aut, cre], Michelle Donzallaz [aut], Andrew Heathcote [aut], Steven Miletić [ctb], Raphael Hartmann [ctb], Karl C. Klauer [ctb], Steven G. Johnson [ctb], Jean M. Linhart [ctb], Brian Gough [ctb], Gerard Jungman [ctb], Rudolf Schuerer [ctb], Przemyslaw Sliwa [ctb], Jason H. Stover [ctb]
Maintainer: Niek Stevenson <niek.stevenson at gmail.com>
BugReports: https://github.com/ampl-psych/EMC2/issues
License: GPL (≥ 3)
URL: https://ampl-psych.github.io/EMC2/, https://github.com/ampl-psych/EMC2
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: EMC2 results

Documentation:

Reference manual: EMC2.pdf
Vignettes: "Simulation-based Calibration" (source, R code)

Downloads:

Package source: EMC2_2.1.0.tar.gz
Windows binaries: r-devel: EMC2_2.1.0.zip, r-release: EMC2_2.1.0.zip, r-oldrel: EMC2_2.1.0.zip
macOS binaries: r-release (arm64): EMC2_2.1.0.tgz, r-oldrel (arm64): EMC2_2.1.0.tgz, r-release (x86_64): EMC2_2.1.0.tgz, r-oldrel (x86_64): EMC2_2.1.0.tgz
Old sources: EMC2 archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=EMC2 to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.