Demonstration R code for some recurrence over text and other categorical series.
Demo coded by: Rick Dale
Shared for: Nonlinear ATI Summer, 2016-2018 in Cincinnati, OH
If you find this code useful we encourage you to cite the crqa library publication:
Coco, M. I. & Dale, R. (2014). Cross-recurrence quantification analysis of categorical and continuous time series: an R package. Frontiers in Quantitative Psychology and Measurement, 5, 510. http://journal.frontiersin.org/article/10.3389/fpsyg.2014.00510/full
For quick start view the PDF ATI_Demo_RStudio.pdf.
Other code samples:
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slidingJRP.R: Illustrating how one can slide recurrence plots (RPs) across each other to obtain a lagged (or "sliding") joint recurrence profile (JRP). This can help overcome the assumption that JRP uses, that recurrences across systems will be aligned simultaneously. Code to help with interesting work of Dr. Shimizu Daichi (Tokyo) and Dr. Mustafa Demir (ASU).
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wordFullExample.R: An example of processing transcript to convert text into numeric series and then perform analysis over it. Also includes an example of LIWC processing for RQA (thanks to Lena Mueller).
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windowedRQAExample.R: Using some sample data from Dr. Kentaro Kodama, this code shows how to set a window size and window shift to obtain a time series of RQA measures.
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handlingSheets.R: Some further sample R code to do windowed recurrence and work with columns of a CSV file (thanks to Dr. Vicki Dawei Jia for these sample data). These data are categorical.
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paramSelectionExample.R: A demonstration of selecting parameters automatically.
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recodedTextWithIdentityColumn.R: Using identity at the front of the text line to create a coded pair of time series to do CRQA with transcripts.
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exampleImageProcessing.R: If you have an image that has an intrinsic temporal axis (e.g., left to right), this script will show you how to use the pixels to convert into a time series (thanks to Dr. Jon Hilpert for the example source images in an educational context).
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Excel conversion example/testBook.R: Demonstration of processing transcripts in Excel to generate different time series (thanks to Dr. Alexia Galati for presenting this example case).
If you are fresh to R (and RStudio) see: https://www.datacamp.com/courses/free-introduction-to-r
If you have just installed RStudio, you need to install the required packages, like this:
install.packages('crqa')
In the code, when you see library(X), where X is some library loaded by the script, ensure that you carry out this procedure for that library as well: install.packages('X').