covEllipses | R Documentation |
The function draws covariance ellipses for one or more groups and optionally
for the pooled total sample. It uses either the classical product-moment
covariance estimate, or a robust alternative, as provided by
cov.rob
. Provisions are provided to do this for more
than two variables, in a scatterplot matrix format.
covEllipses(x, ...)
## S3 method for class 'data.frame'
covEllipses(
x,
group,
pooled = TRUE,
method = c("classical", "mve", "mcd"),
...
)
## S3 method for class 'matrix'
covEllipses(
x,
group,
pooled = TRUE,
method = c("classical", "mve", "mcd"),
...
)
## S3 method for class 'formula'
covEllipses(x, data, ...)
## S3 method for class 'boxM'
covEllipses(x, ...)
## Default S3 method:
covEllipses(
x,
means,
df,
labels = NULL,
variables = 1:2,
level = 0.68,
segments = 60,
center = FALSE,
center.pch = "+",
center.cex = 2,
col = getOption("heplot.colors", c("red", "blue", "black", "darkgreen", "darkcyan",
"brown", "magenta", "darkgray")),
lty = 1,
lwd = 2,
fill = FALSE,
fill.alpha = 0.3,
label.pos = 0,
xlab,
ylab,
vlabels,
var.cex = 2,
main = "",
xlim,
ylim,
axes = TRUE,
offset.axes,
add = FALSE,
...
)
x |
The generic argument. For the default method, this is a list of
covariance matrices. For the |
... |
Other arguments passed to the default method for |
group |
a factor defining groups, or a vector of length
|
pooled |
Logical; if |
method |
the covariance method to be used: classical product-moment
( |
data |
For the |
means |
For the default method, a matrix of the means for all groups
(followed by the grand means, if |
df |
For the default method, a vector of the degrees of freedom for the covariance matrices |
labels |
Either a character vector of labels for the groups, or
|
variables |
indices or names of the response variables to be plotted;
defaults to |
level |
equivalent coverage of a data ellipse for normally-distributed
errors, defaults to |
segments |
number of line segments composing each ellipse; defaults to
|
center |
If |
center.pch |
character to use in plotting the centroid of the data;
defaults to |
center.cex |
size of character to use in plotting the centroid of the
data; defaults to |
col |
a color or vector of colors to use in plotting ellipses —
recycled as necessary A single color can be given, in which case it is used
for all ellipses. For convenience, the default colors for all plots
produced in a given session can be changed by assigning a color vector via
|
lty |
vector of line types to use for plotting the ellipses; the first
is used for the error ellipse, the rest — possibly recycled — for the
hypothesis ellipses; a single line type can be given. Defaults to
|
lwd |
vector of line widths to use for plotting the ellipses; the first
is used for the error ellipse, the rest — possibly recycled — for the
hypothesis ellipses; a single line width can be given. Defaults to
|
fill |
A logical vector indicating whether each ellipse should be filled or not. The first value is used for the error ellipse, the rest — possibly recycled — for the hypothesis ellipses; a single fill value can be given. Defaults to FALSE for backward compatibility. See Details below. |
fill.alpha |
Alpha transparency for filled ellipses, a numeric scalar
or vector of values within |
label.pos |
Label position, a vector of integers (in |
xlab |
x-axis label; defaults to name of the x variable. |
ylab |
y-axis label; defaults to name of the y variable. |
vlabels |
Labels for the variables can also be supplied through this
argument, which is more convenient when |
var.cex |
character size for variable labels in the pairs plot |
main |
main plot label; defaults to |
xlim |
x-axis limits; if absent, will be computed from the data. |
ylim |
y-axis limits; if absent, will be computed from the data. |
axes |
Whether to draw the x, y axes; defaults to |
offset.axes |
proportion to extend the axes in each direction if computed from the data; optional. |
add |
if |
These plot methods provide one way to visualize possible heterogeneity of within-group covariance matrices in a one-way MANOVA design. When covariance matrices are nearly equal, their covariance ellipses should all have the same shape. When centered at a common mean, they should also all overlap.
The can also be used to visualize the difference between classical and robust covariance matrices.
Nothing is returned. The function is used for its side-effect of producing a plot.
Michael Friendly
heplot
, boxM
,
cov.rob
data(iris)
# compare classical and robust covariance estimates
covEllipses(iris[,1:4], iris$Species)
covEllipses(iris[,1:4], iris$Species, fill=TRUE, method="mve", add=TRUE, labels="")
# method for a boxM object
x <- boxM(iris[, 1:4], iris[, "Species"])
x
covEllipses(x, fill=c(rep(FALSE,3), TRUE) )
covEllipses(x, fill=c(rep(FALSE,3), TRUE), center=TRUE, label.pos=1:4 )
# method for a list of covariance matrices
cov <- c(x$cov, pooled=list(x$pooled))
df <- c(table(iris$Species)-1, nrow(iris)-3)
covEllipses(cov, x$means, df, label.pos=3, fill=c(rep(FALSE,3), TRUE))
covEllipses(cov, x$means, df, label.pos=3, fill=c(rep(FALSE,3), TRUE), center=TRUE)
# scatterplot matrix version
covEllipses(iris[,1:4], iris$Species,
fill=c(rep(FALSE,3), TRUE), variables=1:4,
fill.alpha=.1)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.