Package: EMC2
Title: Bayesian Hierarchical Analysis of Cognitive Models of Choice
Version: 3.4.1
Authors@R: 
    c(person("Niek", "Stevenson", email = "niek.stevenson@gmail.com", 
           role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3206-7544")),
      person("Michelle", "Donzallaz", role = c("aut")),
      person("Andrew", "Heathcote", role = c("aut")),
      person("Steven", "Miletić", role = c("aut")),
      person("Luke", "Strickland", role = c("ctb")),
      person("Frank", "Hezemans", role = c("ctb")),
      person("Raphael", "Hartmann", role = c("ctb")),
      person("Karl C.", "Klauer", role=c("ctb")),
      person("Steven G.", "Johnson", role=c("ctb")),
      person("Jean M.", "Linhart", role=c("ctb")),
      person("Brian", "Gough", role=c("ctb")),
      person("Gerard", "Jungman", role=c("ctb")),
      person("Rudolf", "Schuerer", role=c("ctb")),
      person("Przemyslaw", "Sliwa", role=c("ctb")),
      person("Jason H.", "Stover", role=c("ctb")))
Description: 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>.
License: GPL (>= 3)
URL: https://ampl-psych.github.io/EMC2/,
        https://github.com/ampl-psych/EMC2
BugReports: https://github.com/ampl-psych/EMC2/issues
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
VignetteBuilder: knitr
Suggests: testthat (>= 3.0.0), vdiffr, knitr, rmarkdown, DiagrammeR
Config/testthat/edition: 3
Imports: abind, coda, graphics, grDevices, magic, MASS, matrixcalc,
        methods, msm, mvtnorm, parallel, stats, Matrix, Rcpp,
        Brobdingnag, corrplot, colorspace, psych, utils, lpSolve,
        WienR,
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.5.0)
LazyData: true
Config/testthat/parallel: true
Repository: https://ampl-psych.r-universe.dev
Date/Publication: 2026-03-25 13:14:10 UTC
RemoteUrl: https://github.com/ampl-psych/emc2
RemoteRef: HEAD
RemoteSha: 1887e45a6225f6ad29e9016ec17f58c471859301
NeedsCompilation: yes
Packaged: 2026-07-02 09:59:44 UTC; root
Author: Niek Stevenson [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-3206-7544>),
  Michelle Donzallaz [aut],
  Andrew Heathcote [aut],
  Steven Miletić [aut],
  Luke Strickland [ctb],
  Frank Hezemans [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@gmail.com>