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cabootcrs

Constructs bootstrap elliptical confidence regions for the plotted points in simple and multiple correspondence analysis. These differ from other approaches in that they are explicitly designed as confidence regions for the locations of the population points when projected onto the observed sample axes. The algorithm for multiple CA contains a new method to correct for the well-known distortions caused by the diagonal of the Burt matrix.

Use

For 2-way data presented in this case as a contingency table, perform simple CA and produce plots with confidence regions

theresults <- cabootcrs(thedata)

For p-way data, presented in this case as an n individuals by p variables matrix giving category memberships for each individual, perform multiple CA and produce plots with confidence regions

theresults <- cabootcrs(thedata,catype="mca")

Installing

From CRAN, with

install.packages("cabootcrs")

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Version

Install

install.packages('cabootcrs')

Monthly Downloads

296

Version

2.1.0

License

GPL-3

Maintainer

TJ Ringrose

Last Published

March 2nd, 2022

Functions in cabootcrs (2.1.0)

SuicideData

Suicide data
OsteoData

Osteoarchaeological data with categories given as numbers
OsteoDataNames

Osteoarchaeological data with named categories
DreamData223by3

Maxwell's dream data set with added totally random column
addsupplementary

Calculate coordinates for supplementary points, with option to add to the currently selected plot.
cabasicresults-class

A class containing the basic results from CA
allvarscovs

Extract all variances and covariances in readable form as a data frame
getindicator

Converting a data matrix into an indicator matrix
cabootcrs-package

Bootstrap Confidence Regions for Simple and Multiple Correspondence Analysis
cabootcrs

Calculate category point variances using bootstrapping
myresamplefn

Example of a user-generated resampling routine.
NishData

Nishisato's Singapore data
DreamDataNames

Maxwell's dream data set, using full original labels
cabootcrsresults-class

A class containing the results from CA with bootstrapping
getCT

Converting a data matrix into a contingency table
convert

Converting a data matrix from one format into another
covmat

Extract a single 2 by 2 covariance matrix
getBurt

Converting a data matrix into a Burt matrix
rearrange

Rearranges bootstrap axes by comparing to sample axes
settingsinertias

Internal function to be used by printca and summaryca
sca

Performs standard Correspondence Analysis calculations
rearrange_old

Old and rubbish algorithm to rearrange bootstrap axes by comparing to sample axes
summaryca

Prints brief 2-d results, with standard deviations
getdoubled

Converting a data matrix into a doubled matrix
reflectaxes

Reflect coordinates for chosen axes
reordercategories

Reorder categories for chosen variable in MCA case only
AsbestosData

Asbestos data
AttachmentData

van Ijzendoorn's attachment data
printca

Prints reasonably full results, including variances
plotca

Plotting results with confidence regions
DreamData

Maxwell's dream data set, with simplified labels