plotcorr {ellipse} | R Documentation |
This function plots a correlation matrix using ellipse-shaped glyphs for each entry. The ellipse represents a level curve of the density of a bivariate normal with the matching correlation.
plotcorr(corr, outline = TRUE, col = 'grey', numbers = FALSE, type = c("full","lower","upper"), diag = (type == "full"), bty = "n", axes = FALSE, xlab = "", ylab = "", asp = 1, cex.lab = par("cex.lab"), cex = 0.75*par("cex"), mar = 0.1 + c(2,2,4,2), ...)
corr |
A matrix containing entries between |
outline |
Whether the ellipses should be outlined in the default colour. |
col |
Which colour(s) to use to fill the ellipses. |
numbers |
Whether to plot numerical correlations in place of ellipses. If
numbers is |
type |
Character. Plot |
diag |
Logical. Plot diagonal elements or not. |
bty, axes, xlab, ylab, asp, mar, cex.lab, ... |
Graphical parameters
which will be passed to |
cex |
Graphical parameter
which will be passed to |
The ellipses being plotted will be tangent to a unit character square,
with the shape chosen to match the required correlation. If numbers = FALSE
,
the col
vector will be recycled to colour each of the ellipses; if
TRUE
, it will be ignored.
Duncan Murdoch; Gregor Gorjanc suggested the type
and diag
options.
Murdoch, D.J. and Chow, E.D. (1996). A graphical display of large correlation matrices. The American Statistician 50, 178-180.
save.par <- par(ask = interactive()) # Plot the correlation matrix for the mtcars data full model fit data(mtcars) fit <- lm(mpg ~ ., mtcars) plotcorr(summary(fit, correlation = TRUE)$correlation) # Plot a second figure with numbers in place of the # ellipses plotcorr(summary(fit, correlation = TRUE)$correlation, numbers = TRUE) # Colour the ellipses to emphasize the differences. The color range # is based on RColorBrewer's Reds and Blues (suggested by Gregor Gorjanc) corr.mtcars <- cor(mtcars) ord <- order(corr.mtcars[1,]) xc <- corr.mtcars[ord, ord] colors <- c("#A50F15","#DE2D26","#FB6A4A","#FCAE91","#FEE5D9","white", "#EFF3FF","#BDD7E7","#6BAED6","#3182BD","#08519C") plotcorr(xc, col=colors[5*xc + 6]) plotcorr(xc, col=colors[5*xc + 6], type = "upper") plotcorr(xc, col=colors[5*xc + 6], type = "lower", diag = TRUE) par(save.par)