Parallel Constraint Satisfaction (PCS) models are an increasingly common class of models in Psychology, with applications to reading and word recognition (McClelland & Rumelhart, 1981), judgment and decision making (Glöckner & Betsch, 2008; Glöckner, Hilbig, & Jekel, 2014), and several other fields (e.g. Read, Vanman, & Miller, 1997). In each of these fields, they provide a quantitative model of psychological phenomena, with precise predictions regarding choice probabilities, decision times, and often the degree of confidence. This package provides the necessary functions to create and simulate basic Parallel Constraint Satisfaction networks within R.

Documentation

Manual: PCSinR.pdf
Vignette: None available.

Maintainer: Felix Henninger <mailbox at felixhenninger.com>

Author(s): Felix Henninger*

Install package and any missing dependencies by running this line in your R console:

install.packages("PCSinR")

Depends R (>= 3.3.1)
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Package PCSinR
Materials
URL https://github.com/felixhenninger/PCSinR
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Version 0.1.0
Published 2016-10-19
License GPL (>= 3)
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SystemRequirements
NeedsCompilation no
Citation
CRAN checks PCSinR check results
Package source PCSinR_0.1.0.tar.gz