Package: rtmpt
Version: 0.1-19
Title: Fitting RT-MPT Models
Authors@R: c(person("Raphael", "Hartmann", email = "raphael.hartmann@protonmail.com", role = c("aut", "cre")),
             person("Karl C.", "Klauer", email="christoph.klauer@psychologie.uni-freiburg.de", role=c("cph", "aut", "ctb", "ths")),
			 person("Henrik", "Singmann", email="henrik.singmann@warwick.ac.uk", role=c("aut", "ctb", "cph")),
			 person("Jean Marie", "Linhart", email="jlinhart@stata.com", role=c("cph")))
Author: Raphael Hartmann [aut, cre],
  Karl C. Klauer [cph, aut, ctb, ths],
  Henrik Singmann [aut, ctb, cph],
  Jean Marie Linhart [cph]
Maintainer: Raphael Hartmann <raphael.hartmann@protonmail.com>
Depends: R (>= 3.0.0)
Imports: coda, data.table, loo, matrixcalc, methods, stats, stringr,
        truncnorm, utils
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
SystemRequirements: GSL (>=2.3)
Description: Fit response-time extended multinomial processing tree (RT-MPT) models by Klauer and 
			Kellen (2018) <doi:10.1016/j.jmp.2017.12.003>. The RT-MPT class not only incorporate 
			frequencies like traditional multinomial processing tree (MPT) models, but also latencies. This enables it 
			to estimate process completion times and encoding plus motor execution times next to the process probabilities 
			of traditional MPTs. 'rtmpt' is a Bayesian framework and posterior samples are sampled using a Metropolis-Gibbs 
			sampler like the one described in the Klauer and Kellen (2018), but with some modifications. Other than in 
			the original C++ program we use the free and open source GNU Scientific Library (GSL). There is also the 
			possibility to suppress single process completion times.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Packaged: 2020-03-17 15:07:42 UTC; hartmann2
Repository: CRAN
Date/Publication: 2020-03-19 15:10:08 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 06:48:49 UTC; windows
Archs: i386, x64
