tolEllipsePlot {robustbase} | R Documentation

## 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(s)

Peter Filzmoser, Valentin Todorov and Martin Maechler

### See Also

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

### Examples

    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)

[Package robustbase version 0.93-4 Index]