Bootstrap Confidence Regions for Simple and Multiple Correspondence Analysis
Calculate coordinates for supplementary points, with option to add to ...
Extract all variances and covariances in readable form as a data frame
A class containing the basic results from CA
Bootstrap Confidence Regions for Simple and Multiple Correspondence An...
Calculate category point variances using bootstrapping
A class containing the results from CA with bootstrapping
Converting a data matrix from one format into another
Extract a single 2 by 2 covariance matrix
Converting a data matrix into a Burt matrix
Converting a data matrix into a contingency table
Converting a data matrix into a doubled matrix
Converting a data matrix into an indicator matrix
Example of a user-generated resampling routine.
Plotting results with confidence regions
Prints reasonably full results, including variances
Rearranges bootstrap axes by comparing to sample axes
Old and rubbish algorithm to rearrange bootstrap axes by comparing to ...
Reflect coordinates for chosen axes
Reorder categories for chosen variable in MCA case only
Performs standard Correspondence Analysis calculations
Internal function to be used by printca and summaryca
Prints brief 2-d results, with standard deviations
Performs simple correspondence analysis on a two-way contingency table, or multiple correspondence analysis (homogeneity analysis) on data with p categorical variables, and produces bootstrap-based elliptical confidence regions around the projected coordinates for the category points. Includes routines to plot the results in a variety of styles. Also reports the standard numerical output for correspondence analysis.