plotcorr {biostatUZH} | 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.
This is a fork of the original plotcorr
function
from the ellipse package as at version 0.3-8.
The arguments numbers
, type
, and diag
have been
replaced by lower.panel
, upper.panel
, and
diag.panel
similar to pairs
.
This enables displaying numbers in one triangle and ellipses in the
other. However, there is no support for diag = FALSE
in the
original sense of the function.
plotcorr(corr, outline = TRUE, col = TRUE, lower.panel = "ellipse", upper.panel = "number", diag.panel = NULL, 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 (recycled to |
lower.panel, upper.panel, diag.panel |
each panel can be either |
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.
(of this fork) Sebastian Meyer, (of the original version) Duncan Murdoch
Murdoch, D.J. and Chow, E.D. (1996). A graphical display of large correlation matrices. The American Statistician 50, 178-180.
if (requireNamespace("ellipse")) { ## Plot the correlation matrix for the mtcars data full model fit data("mtcars") fit <- lm(mpg ~ ., mtcars) corr.fit <- summary(fit, correlation = TRUE)$correlation plotcorr(corr.fit, col = "gray") ## with default color coding plotcorr(corr.fit, col = TRUE) ## Colour the ellipses and order by correlations with miles/gallon corr.mtcars <- cor(mtcars) ord <- order(corr.mtcars[1,]) xc <- corr.mtcars[ord, ord] colors <- colorRampPalette(c("blue", "white", "red"))(11) plotcorr(xc, col = colors[5*xc + 6]) }