Creates an index plot of the observation weights assigned in the
last iteration of robmlm
. Observations with low weights
have large residual squared distances and are potential multivariate
outliers with respect to the fitted model.
# S3 method for robmlm
plot(x, labels,
id.weight = 0.7, id.pos = 4,
pch = 19,
col = palette()[1], cex = par("cex"),
segments = FALSE,
xlab = "Case index", ylab = "Weight in robust MANOVA", ...)
A "robmlm"
object
Observation labels; if not specified, uses rownames from the original data
Threshold for identifying observations with small weights
Position of observation label relative to the point
Point symbol(s); can be a vector of length equal to the number of observations in the data frame
Point color(s)
Point character size(s)
logical; if TRUE
, draw line segments from 1.o down to the point
x axis label
y axis label
other arguments passed to plot
Returns invisibly the weights for the observations labeled in the plot
# NOT RUN { data(Skulls) sk.rmod <- robmlm(cbind(mb, bh, bl, nh) ~ epoch, data=Skulls) plot(sk.rmod, col=Skulls$epoch) axis(side=3, at=15+seq(0,120,30), labels=levels(Skulls$epoch), cex.axis=1) # Pottery data pottery.rmod <- robmlm(cbind(Al,Fe,Mg,Ca,Na)~Site, data=Pottery) plot(pottery.rmod, col=Pottery$Site, segments=TRUE) # SocialCog data data(SocialCog) SC.rmod <- robmlm(cbind( MgeEmotions, ToM, ExtBias, PersBias) ~ Dx, data=SocialCog) plot(SC.rmod, col=SocialCog$Dx, segments=TRUE) # }