Correspondence Analysis in Archaeology
  • Home
  • Guide by worked examples
    • Aim of Correspondence Analysis
    • Association between rows and columns
    • Number of dimensions useful for data interpretation
    • Interpreting the CA scatterplot: dimensions interpretation
    • Interpreting the CA scatterplot (continued): correlation between row profiles and dimensions
    • Quality of the representation
    • Assembling the whole picture
    • Extension: clustering rows and/or columns
    • Another worked example
  • References
  • CA in R
    • CAinterprTools (R package)
    • R function for various CA scatterplots
    • R function for improved CA scatterplot
    • R function for perceptual-map-like CA scatterplot
    • R function for plotting Pareto chart of categories contribution
    • R Script for CA
    • Additional R Script for CA
    • R Script for the Significance of CA's Dimensions
  • Other Tools for Statistics
    • R package for seriation via CA
    • R function for scalar-stress probability calculation
    • R function for post. prob. for different relations btw 2 Bayesian 14C phases
    • R function for Posterior Probability Density plot
    • R function for binary Logistic Regression
    • R function for binary Logistic Regression internal validation
    • R function for optimism-adjusted AUC
    • R function for Brainerd-Robinson similarity coefficient
    • R function for univariate outliers detection
    • R function for plotting Jenks natural breaks classification
    • R function for permutation-based Chi square test of independence
    • R function for permutation t-test
    • R function for visually displaying Mann-Whitney test
    • R function for visually displaying Kruskal-Wallis test
    • Kruskal-Wallis Excel Template
    • Chi-squared Excel Template
    • Excel Template for Robust Statistics
  • GIS
  • Blog
  • About me
  • Guestbook/Comments
'CAinterprTools': R package for visual aid to Correspondence Analysis interpretation

Some of the features of the R script for CA (described in this site) have been turned into an R package. As of July 2018, the package is  available from CRAN and can therefore easily installed into R. For other info, and for download statistics, see the RDocumentation website.

Besides implementing some of the features of my CA script, the package dramatically expands the available facilities  to get a visual aid to the interpretation of the results of Correspondence Analysis. Among other things, the package allows to
calculate the significance of the CA dimensions and of the total inertia by means of  a permutation test.

The package is also described in an article of mine published in Elsevier's SoftwareX journal (LINK).

If you want to cite my package, you may use the following format:

Alberti G, CAinterprTools: An R package to help interpreting Correspondence Analysis’ results, SoftwareX, Volumes 1–2, September 2015, Pages 26-31, ISSN 2352-7110, http://dx.doi.org/10.1016/j.softx.2015.07.001.​

Please note that the package has been improved several times since 2015. A description of the facilities it provides (as of version 1.0.0) can be found in the PDF below.
Package installation:

if you are using RStudio, you can use the Tools > Install packages... menu (as shown to the right; click to enlarge); otherwise, you can simply use the following command:


install.packages("CAinterprTools")
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