Comparison Plots for Covariance/Correlation Models

DESCRIPTION:

Creates a set plots useful for comparing fitted covariance/correlation models stored in a fit.models object with virtual class covfm.

USAGE:

plot.covfm(x, which.plots="all", chisq.percent=0.975, id.n=3,
           variables, ...)

REQUIRED ARGUMENTS:

x
a fit.models object with virtual class covfm.

OPTIONAL ARGUMENTS:

which.plots
either "ask", "all", or an integer vector specifying which plots to draw. If which.plots is an integer vector, use the plot numbers given here (or in the "ask" menu). The plot options are (2) Eigenvalues of Covariance Estimate, (3) Sqrt of Mahalanobis Distances, (4) Distance - Distance Plot, and (5) Ellipses Matrix.
chisq.percent
p-value used to calculate the outlier threshold.
id.n
number of outliers identified in plots.
variables
an integer vector specifying which eigenvalues to display in the screeplot. The default is to display the 10 largest eigenvalues.

VALUE:

x is invisibly returned.

SIDE EFFECTS:

The selected plots are drawn on a graphics device.

REFERENCES:

Murdoch and Chow (1996). A Graphical Display of Large Correlation Matrices. American Statistician.

SEE ALSO:

, .

EXAMPLES:

Robust <- covRob(woodmod.dat)
Classical <- cov(woodmod.dat)
# wood.fm is a fit.models object with virtual class covfm:
wood.fm <- fit.models(Robust, Classical)
plot(wood.fm)