cpairs {gclus} | R Documentation |
This function draws a scatterplot matrix of data. Variables may be reordered and panels colored in the display.
cpairs(data, order = NULL, panel.colors = NULL, border.color = "grey70", show.points = TRUE, ...)
data |
a numeric matrix |
order |
the order of variables. Default is the order in data. |
panel.colors |
a matrix of panel colors. If supplied, dimensions should match those of the pairs plot. Diagonal entries are ignored. |
border.color |
used for panel border. |
show.points |
If FALSE, no points are drawn. |
... |
graphical parameters passed to pairs.default . |
Catherine B. Hurley
Hurley, Catherine B. “Clustering Visualisations of Multidimensional Data”, to appear in JCGS.
pairs
, cparcoord
,
dmat.color
,colpairs
, order.single
.
data(USJudgeRatings) judge.cor <- cor(USJudgeRatings) judge.color <- dmat.color(judge.cor) # Colors variables by their correlation. cpairs(USJudgeRatings,panel.colors=judge.color,pch=".",gap=.5) judge.o <- order.single(judge.cor) # Reorder variables so that those with highest correlation # are close to the diagonal. cpairs(USJudgeRatings,judge.o,judge.color,pch=".",gap=.5) # Specify your own color scheme judge.color <- dmat.color(judge.cor, breaks=c(-1,0,.5,.9,1), colors = cm.colors(4)) data(bank) # m is a homogeneity measure of each pairwise variable plot m <- -colpairs(scale(bank[,-1]), partition.crit,gfun=gave,groups=bank[,1]) # Color panels by level of m and reorder variables so that # pairs with high m are near the diagonal. Panels shown # in pink have the highest amount of group homogeneity, as measured by # gave. cpairs(bank[,-1],order=order.single(m), panel.colors=dmat.color(m), gap=.3,col=c("purple","black")[bank[,"Status"]+1], pch=c(5,3)[bank[,"Status"]+1])