[R] Plotting Bivariate Normal Data
Martin Maechler
maechler at stat.math.ethz.ch
Mon Oct 25 08:43:12 CEST 2004
>>>>> "JohnF" == John Fox <jfox at mcmaster.ca>
>>>>> on Sun, 24 Oct 2004 12:37:09 -0400 writes:
JohnF> Dear Sarah, If the data are allegedly bivariate
JohnF> normal, then they are probably two vectors, not
JohnF> one. Assuming that this is the case, I know of
JohnF> nothing quite as neat as a univariate QQ plot to
JohnF> check visually for bivariate normality (perhaps
JohnF> someone else has a suggestion here), but you could
JohnF> superimpose bivariate-normal contours on a
JohnF> scatterplot of the data, perhaps along with a
JohnF> bivariate density estimate. The car and ellipse
JohnF> packages can do the former, while the locfit and sm
JohnF> packages (and possibly others) can do the latter.
Since one of the more severe and common deviations from
normality is "long tailed"ness (in all it's vaguety), we have
been recommending to QQ-plot mahalanobis distances against chi
squared quantiles - even before looking at the univariate
QQ plots.
Exactly for this reason, in R,
example(mahalanobis)
shows a version of how to do this!
Martin Maechler, ETH Zurich
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