View source: R/defineclassesandfunctions.R
covmat | R Documentation |
covmat
extracts a 2 by 2 covariance matrix for one data point on two dimensions,
allowing the confidence ellipse to be plotted
covmat(x, i, thing = "column", axis1 = 1, axis2 = 2, show = TRUE)
x |
An object of class |
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
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 |
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
An object of class "matrix"
(square symmetric, 2 by 2)
cabootcrs-package
, cabootcrs
, allvarscovs
,
cabootcrsresults
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)
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