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robustbase (version 0.99-4-1)

tolEllipsePlot: Tolerance Ellipse Plot

Description

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.

Usage

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"))

Arguments

x

a two dimensional matrix or data frame.

m.cov

an object similar to those of class "mcd"; however only its components center and cov will be used. If missing, the MCD will be computed (via covMcd()).

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 cutoff is used.

classic

whether to plot the classical distances as well, FALSE by default.

tol

tolerance to be used for computing the inverse, see solve. Defaults to 1e-7.

xlab, ylab, main

passed to plot.default.

txt.leg, col.leg, lty.leg

character vectors of length 2 for the legend, only used if classic = TRUE.

Author

Peter Filzmoser, Valentin Todorov and Martin Maechler

See Also

covPlot which calls tolEllipsePlot() when desired. ellipsoidhull and predict.ellipsoid from package cluster.

Examples

Run this code
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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