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biplot drawing conc ellipses

3 messages · T. Murlidharan Nair, Pierre BADY, Jari Oksanen

T. Murlidharan Nair
# 
Is there an option to draw concentration ellipses in biplots ? It seems
really nice to summarize large number of points of each group.

Cheers../ Murli
Pierre BADY
# 
Hi all,

you can see in the library(ade4).
there is  a nice graphical function called ‘s.class’.

Example for a principal components analysis:
?s.class

data(meaudret)
pca1 <- dudi.pca(meaudret$mil, scan = FALSE, nf = 4)
# plot row coordinates 
s.class(pca1$li, meaudret$plan$dat, sub = "Principal Component Analysis",add.
p=F,col=c(1,2,3,4),cstar=0)
# add principal axes
s.arrow(pca1$c1,clabel=0.7,add.p=T)


# &#8220;&#8230;  'scatter.dudi' is a factorial map of individuals and the
# projection of the vectors of the canonical basis multiplied by a
# constante of rescaling. &#8230;&#8221;

?scatter.dudi
scatter.dudi(pca1,clab.row=0)
s.class(pca1$li, meaudret$plan$dat, sub = "Principal Component Analysis",add.
p=T,col=c(1,2,3,4), cstar=0)

hope this helps,


P.BADY

Quoting "T. Murlidharan Nair" <nair at sdsc.edu>:
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Jari Oksanen
#
On Thu, 2004-11-04 at 22:44, T. Murlidharan Nair wrote:
Murli,

If you mean biplot.prcomp function in stats package, and you want to
draw the "concentration ellipses" for row scores, the answer probably is
"not easily". Technically, the problem is that arrows for loadings are
drawn after labels for rowscores, and the scaling used for drawing row
scores is lost in the process. If you try to add points or segments to
the existing plots, you should use the scaling for arrows on sides 3 and
4 (top and right). If you want to add something for row scores, you just
don't have information on co-ordinates. I didn't check biplot.princomp,
but the situation may be similar there. 

Drawing of ellipsoids is possible in some alternative packages. You
already got a hint of ade4. In addition, vegan has pca as a special case
of its rda function, and there you have tools like ordiellipse (using
the ellipse package), ordispider and ordihull to display the variability
within factor levels. However, vegan doesn't have biplots like
biplot.prcomp, i.e. with arrows for loadings, Moreover, scaling of
results is different. 

It seems that the only thing you can do is to write your sweet on biplot
function. 

cheers, jari oksanen