kollaR: Event Classification, Visualization and Analysis of Eye Tracking
Data
Functions for analysing eye tracking data, including event detection, visualizations and area of interest (AOI) based analyses.
The package includes implementations of the IV-T, I-DT, adaptive velocity threshold, and Identification by two means clustering (I2MC) algorithms.
See separate documentation for each function. The principles underlying I-VT and I-DT algorithms are described in Salvucci & Goldberg (2000,\doi{10.1145/355017.355028}).
Two-means clustering is described in Hessels et al. (2017, \doi{10.3758/s13428-016-0822-1}).
The adaptive velocity threshold algorithm is described in Nyström & Holmqvist (2010,\doi{10.3758/BRM.42.1.188}).
See a demonstration in the URL.
| Version: |
1.1.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
dplyr, ggplot2, zoo, ggforce, tidyr, ggpubr, jpeg, patchwork, shiny, plotly, base64enc, magick, scales |
| Published: |
2025-05-07 |
| DOI: |
10.32614/CRAN.package.kollaR |
| Author: |
Johan Lundin Kleberg [aut, cre] |
| Maintainer: |
Johan Lundin Kleberg <johan.lundin.kleberg at su.se> |
| License: |
GPL-3 |
| URL: |
https://drjohanlk.github.io/kollaR/demo.html |
| NeedsCompilation: |
no |
| Citation: |
kollaR citation info |
| CRAN checks: |
kollaR results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=kollaR
to link to this page.