Bootstrap Confidence Regions for Simple and Multiple Correspondence Analysis

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Documentation for package ‘cabootcrs’ version 2.1.0

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cabootcrs-package Bootstrap Confidence Regions for Simple and Multiple Correspondence Analysis
addsupplementary Calculate coordinates for supplementary points, with option to add to the currently selected plot.
allvarscovs Extract all variances and covariances in readable form as a data frame
AsbestosData Asbestos data
AttachmentData van Ijzendoorn's attachment data
cabasicresults-class A class containing the basic results from CA
cabootcrs Calculate category point variances using bootstrapping
cabootcrsresults-class A class containing the results from CA with bootstrapping
convert Converting a data matrix from one format into another
covmat Extract a single 2 by 2 covariance matrix
DreamData Maxwell's dream data set, with simplified labels
DreamData223by3 Maxwell's dream data set with added totally random column
DreamDataNames Maxwell's dream data set, using full original labels
getBurt Converting a data matrix into a Burt matrix
getCT Converting a data matrix into a contingency table
getdoubled Converting a data matrix into a doubled matrix
getindicator Converting a data matrix into an indicator matrix
myresamplefn Example of a user-generated resampling routine.
NishData Nishisato's Singapore data
OsteoData Osteoarchaeological data with categories given as numbers
OsteoDataNames Osteoarchaeological data with named categories
plotca Plotting results with confidence regions
printca Prints reasonably full results, including variances
rearrange Rearranges bootstrap axes by comparing to sample axes
rearrange_old Old and rubbish algorithm to rearrange bootstrap axes by comparing to sample axes
reflectaxes Reflect coordinates for chosen axes
reordercategories Reorder categories for chosen variable in MCA case only
sca Performs standard Correspondence Analysis calculations
settingsinertias Internal function to be used by printca and summaryca
SuicideData Suicide data
summaryca Prints brief 2-d results, with standard deviations