plot-methods {rrcov} | R Documentation |
Shows the Mahalanobis distances based on robust and/or classical estimates of the location and the covariance matrix in different plots. The following plots are available:
- index plot of the robust and mahalanobis distances
- distance-distance plot
- Chisquare QQ-plot of the robust and mahalanobis distances
- plot of the tolerance ellipses (robust and classic)
- Scree plot - Eigenvalues comparison plot
## S4 method for signature 'CovClassic': plot(x, which = c("all","distance","qqchi2","tolellipse","screeplot"), ask=(which=="all" && dev.interactive()), cutoff, id.n, tol=1e-7, ...) ## S4 method for signature 'CovRobust': plot(x, which = c("all","dd","distance","qqchi2","tolellipse","screeplot"), classic=FALSE, ask=(which=="all" && dev.interactive()), cutoff, id.n, tol=1e-7, ...)
x |
an object of class "Cov" or "CovRobust" |
which |
Which plot to show? See Details for description of the options. Default is which ="all". |
classic |
whether to plot the classical distances too. Default is classic =FALSE. |
ask |
logical; if 'TRUE', the user is asked before each plot, see 'par(ask=.)'.
Default is ask = which=="all" && dev.interactive() . |
cutoff |
The cutoff value for the distances. |
id.n |
Number of observations to identify by a label. If not supplied, the number of observations with distance larger than cutoff is used. |
tol |
tolerance to be used for computing the inverse see 'solve'. Default is tol = 10e-7 |
... |
other parameters to be passed through to plotting functions. |
x
.x
.data(hbk) hbk.x <- data.matrix(hbk[, 1:3]) cv <- CovClassic(hbk.x) plot(cv) rcv <- CovMest(hbk.x) plot(rcv)