Description: MPTinR provides a user-friendly way for the analysis of
multinomial processing tree (MPT) models (e.g., Riefer, D. M.,
and Batchelder, W. H. [1988]. Multinomial modeling and the
measurement of cognitive processes. Psychological Review, 95,
318-339) for single and multiple datasets. The main functions
perform model fitting and model selection. Model selection can
be done using AIC, BIC, or the Fisher Information Approximation
(FIA) a measure based on the Minimum Description Length (MDL)
framework. The model and restrictions can specified in external
files or within an R script in an intuitive syntax. The
'classical' .EQN file format for model files is also supported.
Besides MPTs, MPTinR can fit a wide variety of other cognitive
models such as SDT models (see fit.model). MPTinR supports
multicore fitting using the snowfall package.

multicore fitting using the snowfall package. MPTinR can
generate data generating from a model for e.g., parametric

bootstrap and plot predicted versus observed data.

Author: Henrik Singmann, David Kellen, and Christian Mueller
multicore fitting and FIA calculation using the snowfall
package. MPTinR can generate data generating from a model for
e.g., parametric bootstrap and plot predicted versus observed
Depends: R (>= 2.11.0), numDeriv, RcppEigen, Rcpp

Authors@R: c(person("Henrik", "Singmann", role = c("aut", "cre"),
person("David", "Kellen", role =  "aut"),
person("Quentin", "Gronau", role =  "aut"),
person("Christian", "Mueller", role =  "ctb"),
person("Akhil S", "Bhel", role =  "ctb"))
Description: Provides a user-friendly way for the analysis of multinomial processing tree (MPT) models (e.g.,  Riefer, D. M., and Batchelder, W. H. [1988]. Multinomial modeling and the measurement of cognitive processes. Psychological Review, 95, 318-339) for single and multiple datasets. The main functions perform model fitting and model selection. Model selection can be done using AIC, BIC, or the Fisher Information Approximation (FIA) a measure based on the Minimum Description Length (MDL) framework. The model and restrictions can be specified in external files or within an R script in an intuitive syntax or using the context-free language for MPTs. The 'classical' .EQN file format for model files is also supported. Besides MPTs, this package can fit a wide variety of other cognitive models such as SDT models (see fit.model). It also supports multicore fitting and FIA calculation (using the snowfall package), can generate or bootstrap data for simulations, and plot predicted versus observed data.
Imports: numDeriv, Brobdingnag, Rcpp, stats, utils