rtmpt

R package for fitting Response-Time extended Multinomial Processing Tree (RT-MPT) models by Klauer and Kellen (2018)

Description

The model class RT-MPT incorporate response frequencies and response latencies. This enables the estimation of

In total we have for each process one probability parameter and two process completion times (for each outcome of the process one).

rtmpt has two sub-model classes: the exponential RT-MPT uses a Metropolis-within-Gibbs sampler and builds on the C++ code by Klauer and Kellen (2018) with some modifications. The diffusion RT-MPT uses a Hamiltonian-Within-Gibbs sampler and builds on the C++ code by Klauer, Hartmann, and Meyer-Grant (submitted manuscript).

In the exponential RT-MPT (short ertmpt) model class it is possible to

In the diffusion RT-MPT (short drtmpt) model class it is possible to

For more information about the functionalities check the help files or the vignette of the package.

Installation

CRAN

An installation via CRAN is now possible. Write in the command line in R:

    install.packages("rtmpt")

Alternative instructions

Linux

Before installing the R package rtmpt you need to install the latest version of the GNU Scientific Library (GSL):

  1. Download the latest *tar.gz file from GSL
  2. Unzip the file
  3. Assuming you downloaded version 2.5 and unziped the file to ~/Downloads/gsl-2.5, open terminal and change directory via $ cd ~/Downloads/gsl-2.5
  4. Execute the following lines:
    ./configure
    make
    sudo make install
    

For some Linux distributions it is necessary to run sudo ldconfig -v in the terminal before installing rtmpt.

Installing rtmpt is possible either

MacOS

Before installing the R package rtmpt from source you need to do the following:

  1. If not already installed, install Homebrew
  2. Install GSL via Homebrew using terminal and command brew install gsl
  3. Install Xcode from the App Store and then install the Command Line Tools using xcode-select --install
  4. If you use MacOS Mojave, make sure to also run the following command:
    open /Library/Developer/CommandLineTools/Packages/macOS_SDK_headers_for_macOS_10.14.pkg
    
  5. Also execute brew install gcc in your terminal.
  6. Check via ls /usr/local/bin/ what endings the gcc/g++ executables have (in my case -9)
  7. If ~/.R/Makevars does not already exist, create it with mkdir ~/.R/ and touch ~/.R/Makevars
  8. Use open ~/.R/Makevars to write the following in the Makevars file (assuming your gcc/g++ executables have the ending -9):
    CC=/usr/local/bin/gcc-9
    CXX=/usr/local/bin/g++-9
    CXX11=/usr/local/bin/g++-9
    
    and save.

Installing the rtmpt package:

This is possible either

Citation

If you want to cite this package write

Hartmann, R., Johannsen, L., & Klauer, K. C. (2020). rtmpt: An R package for fitting response-time extended multinomial processing tree models. Behavior Research Methods, 52(3), 1313–1338. doi: 10.3758/s13428-019-01318-x

or use the BibTeX code:

@article{Hartmann_2020,
	doi = {10.3758/s13428-019-01318-x},
	url = {https://doi.org/10.3758%2Fs13428-019-01318-x},
	year = 2020,
	month = {may},
	publisher = {Springer Science and Business Media {LLC}},
	volume = {52},
	number = {3},
	pages = {1313--1338},
	author = {Raphael Hartmann and Lea Johannsen and Karl Christoph Klauer},
	title = {rtmpt: An R package for fitting response-time extended multinomial processing tree models},
	journal = {Behavior Research Methods}
}

References

Klauer, K. C., & Kellen, D. (2018). RT-MPTs: Process models for response-time distributions based on multinomial processing trees with applications to recognition memory. Journal of Mathematical Psychology, 82, 111-130. 111–130. doi: 10.1016/j.jmp.2017.12.003

Hartmann, R., Johannsen, L., & Klauer, K. C. (2020). rtmpt: An R package for fitting response-time extended multinomial processing tree models. Behavior Research Methods, 52(3), 1313–1338. doi: 10.3758/s13428-019-01318-x

Hartmann, R., & Klauer, K. C. (2020). Extending RT-MPTs to enable equal process times. Journal of Mathematical Psychology, 96, 102340. doi: 10.1016/j.jmp.2020.102340

Galassi, M., Davies, J., Theiler, J., Gough, B., Jungman, G., Alken, P., . . . Ulerich, R. (2018). GNU scientific library [Computer software]. Retrieved from http://www.gnu.org/software/gsl/