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Tutorials and tools to help with RQA and CRQA in R.

License: MIT License

R 100.00%
recurrence-quantification-analysis recurrence-plot plotting visualization visualization-tools ggplot2 tutorial cross-recurrence cross-recurrence-plot r

crqa-tools-and-more's Introduction

Resources for nonlinear analyses

Tools and tutorials to help with recurrence quantification analysis (RQA), cross-recurrence quantification analysis (CRQA), and detrended fluctuation analysis (DFA).

Tutorials

Here are the tutorials that are currently available:

  • ./tutorials/tutorial-categorical_recurrence.R: Tutorial for categorical recurrence quantification analysis and cross-recurrence quantification analysis in R.
  • ./tutorials/tutorial-continous_recurrence.R: Tutorial for continuous recurrence quantification analysis and cross-recurrence quantification analysis in R, including conducting manual parameter search.
  • ./tutorials/tutorial-dfa.R: Tutorial for detrended fluctuation analysis.

Data for the tutorials are included in the ./tutorials/data/ directory.

Acknowledgements for example data

The informative text on chickens comes from the "Chicken" entry from Wikipedia (https://en.wikipedia.org/wiki/Chicken). The poetic text on chickens comes from "Last Night I Dreamed of Chickens" by Jack Prelutsky (https://poets.org/poem/last-night-i-dreamed-chickens).

The converted versions of the text files come thanks to Rick Dale's free "Text Converter" tool.

The data for the fractal analysis are courtesy of the U.S. National Oceanic and Atmospheric Association's Climate Data Online API from the National Centers for Environmental Information.

Tools

Here are the tools that are currently available:

  • Visualizations
    • ./tools/create-recurrence-plots-ggplot.r: Create recurrence plot with qplot function from ggplot2 package
    • ./tools/create-recurrence-plots-standard.R: Create recurrence plot with standard plot function

Dependencies

To run these, you will need the following R packages:

  • crqa (Coco & Dale, 2014, Frontiers in Psychology)
  • tidyr
  • nonlinearTseries
  • tseriesChaos
  • ggplot2

Contributing

Contributions are always welcome! Just submit a pull request to get started.

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