covmat {cabootcrs}

Extract a single 2 by 2 covariance matrix

Description

covmat extracts a 2 by 2 covariance matrix for one data point on two dimensions, allowing the confidence ellipse to be plotted

Usage

covmat(x, i, thing = "column", axis1 = 1, axis2 = 2, show = TRUE)

Arguments

x

An object of class cabootcrsresults

i

The number of the row or column, note that in MCA this will be the number of the variable category (e.g. for p=3 variables with 5 categories each, column 8 is the 3rd category of the 2nd variable)

thing

Whether to extract the covariance matrix for the i-th

"row"

row, or

"column"

column

Note that default is "column" as this is more convenient for MCA

axis1

First axis for which (co)variances are required

axis2

Second axis for which (co)variances are required

show

If TRUE then print the extracted covariance matrix

Details

This can be used with the ellipse() package to add the confidence ellipse to a picture from another package

Example: confidence ellipse for row or column i on axes 1,2 from cabootcrs() output Results is:

lines( ellipse(x=covmat(Results,i,"row",1,2,FALSE), centre=Results@Rowprinccoord[i,cbind(1,2)], npoints=1000), cex=1, pch=".", col="blue")
lines( ellipse(x=covmat(Results,i,"column",1,2,FALSE), centre=Results@Colprinccoord[i,cbind(1,2)], npoints=1000), cex=1, pch=".", col="blue")

Note that reflectaxes will be needed if cabootcrs() and ca() axes are reflected with respect to each other

Value

An object of class "matrix" (square symmetric, 2 by 2)

See Also

cabootcrs-package, cabootcrs, allvarscovs, cabootcrsresults

Examples

results <- cabootcrs(DreamData, showresults=FALSE)
row2covmataxes12 <- covmat(results,2,"row")
col3covmataxes23 <- covmat(results,3,"column",2,3)

## Not run: 

# There are now 3 variables with 5,4,3 categories, hence 12 columns
resultsmca <- cabootcrs(DreamData223by3, catype="mca", showresults=FALSE)
row2covmataxes12mca <- covmat(resultsmca,2,"column")
col3covmataxes23mca <- covmat(resultsmca,8,"column",2,3)
newvarcat2covmataxes12mca <- covmat(resultsmca,11,"column")


# Use ellipse() to put confidence regions around row points on a plot produced by ca().
# Note that reflectaxes() will be needed if cabootcrs() and ca() axes
# are reflected with respect to each other

library(ca)
library(ellipse)
TheData <- DreamData
Results <- cabootcrs(TheData, showresults=FALSE)
caResults <- ca(TheData)
plot(caResults)
for (i in 1:dim(TheData)[1]) {
  lines( ellipse(x=covmat(Results,i,"row",1,2,FALSE),
                 centre=Results@Rowprinccoord[i,cbind(1,2)], npoints=1000),
        cex=1, pch=".", col="blue")
}

## End(Not run)