Learn R Programming

PCSinR

The PCSinR package contains all necessary functions for building and simulation Parallel Constraint Satisfaction (PCS) network models within R.

PCS models are an increasingly used framework throughout psychology: They provide quantitative predictions in a variety of paradigms, ranging from word and letter recognition, for which they were originally developed (McClelland & Rumelhart, 1981; Rumelhart & McClelland, 1982), to complex judgments and decisions (Glöckner & Betsch, 2008; Glöckner, Hilbig, & Jekel, 2014), and many other applications besides.

Installation

  • The current stable version is available via CRAN, and can be installed by running install.packages("PCSinR").
  • You can install the latest development version directly from GitHub with the devtools package. To do so, please run devtools::install_github("felixhenninger/PCSinR@master").

Usage

The functions in this package simulate a PCS network, given an interconnection matrix. Methods for creating such a matrix from the most common models are forthcoming.

Once a connection matrix has been specified, the model can be simulated easily using the most common parameter set.

require(PCSinR)
#> Loading required package: PCSinR

interconnections <- matrix(
  c( 0.0000,  0.1015,  0.0470,  0.0126,  0.0034,  0.0000,  0.0000,
     0.1015,  0.0000,  0.0000,  0.0000,  0.0000,  0.0100, -0.0100,
     0.0470,  0.0000,  0.0000,  0.0000,  0.0000,  0.0100, -0.0100,
     0.0126,  0.0000,  0.0000,  0.0000,  0.0000,  0.0100, -0.0100,
     0.0034,  0.0000,  0.0000,  0.0000,  0.0000, -0.0100,  0.0100,
     0.0000,  0.0100,  0.0100,  0.0100, -0.0100,  0.0000, -0.2000,
     0.0000, -0.0100, -0.0100, -0.0100,  0.0100, -0.2000,  0.0000 ),
  nrow=7
)

result <- PCS_run_from_interconnections(interconnections)

A common simulation result concerns the number of iterations needed until convergence is reached.

result$convergence
#> default 
#>     116

The output also contains a log of the model states across all iterations. Here, we examine just the final state.

result$iterations[nrow(result$iterations),]
#>     iteration     energy node_1    node_2    node_3    node_4      node_5    node_6     node_7
#> 117       116 -0.2916358      1 0.5293124 0.3669084 0.1906411 -0.07023219 0.5477614 -0.5477614

General Information

The PCSinR package is developed and maintained by Felix Henninger. It is published under the GNU General Public License (version 3 or later). The NEWS file documents the most recent changes.

This work was supported by the University of Mannheim’s Graduate School of Economic and Social Sciences, which is funded by the German Research Foundation.

Copy Link

Version

Install

install.packages('PCSinR')

Monthly Downloads

113

Version

0.1.0

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Maintainer

Last Published

October 19th, 2016

Functions in PCSinR (0.1.0)

PCS_run_from_interconnections

Simulate the run of a PCS model based on only the interconnection matrix
PCSinR

PCS: Parallel Constraint Satisfaction networks in R
PCS_run

Simulate the run of a PCS model
PCS_convergence_McCandR

Check a PCS network for convergence