Tolerance Ellipse Plot
Plots the 0.975 tolerance ellipse of the bivariate data set x
.
The ellipse is defined by those data points whose distance
is equal to the squareroot of the 0.975 chisquare quantile
with 2 degrees of freedom.
tolEllipsePlot(x, m.cov = covMcd(x), cutoff = NULL, id.n = NULL, classic = FALSE, tol = 1e-07, xlab = "", ylab = "", main = "Tolerance ellipse (97.5%)", txt.leg = c("robust", "classical"), col.leg = c("red", "blue"), lty.leg = c("solid","dashed"))
x |
a two dimensional matrix or data frame. |
m.cov |
an object similar to those of class |
cutoff |
numeric distance needed to flag data points outside the ellipse. |
id.n |
number of observations to be identified by a label. If
not supplied, the number of observations with distance larger than
|
classic |
whether to plot the classical distances as well,
|
tol |
tolerance to be used for computing the inverse, see
|
xlab, ylab, main |
passed to |
txt.leg, col.leg, lty.leg |
character vectors of length 2 for the
legend, only used if |
Peter Filzmoser, Valentin Todorov and Martin Maechler
covPlot
which calls tolEllipsePlot()
when
desired.
ellipsoidhull
and
predict.ellipsoid
from package cluster.
data(hbk) hbk.x <- data.matrix(hbk[, 1:3]) mcd <- covMcd(hbk.x) # compute mcd in advance ## must be a 2-dimensional data set: take the first two columns : tolEllipsePlot(hbk.x[,1:2]) ## an "impressive" example: data(telef) tolEllipsePlot(telef, classic=TRUE)
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