PCSinR
0.2.0Parallel Constraint Satisfaction Networks in R
Overview
Parallel Constraint Satisfaction (PCS) models are an increasingly common class of models in Psychology, with applications to reading and word recognition (McClelland & Rumelhart, 1981; \doi{10.1037/0033-295X.88.5.375}), judgment and decision making (Glöckner & Betsch, 2008 \doi{10.1017/S1930297500002424}; Glöckner, Hilbig, & Jekel, 2014 \doi{10.1016/j.cognition.2014.08.017}), and several other fields. 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.
Install
Health
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-2614 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-03-100 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 88%
- Return-value docs
- 33%
- References docs
- 25%
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Dependencies
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Code & Tests
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.2.0Latest
- 0.1.02026-03-10
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2016-10-19
- Total releases
- 2 / 10 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.3.1
- Download size
- 13 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet