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library(fsdaR)
## Call of spmplot() without optional parameters.
## Iris data: scatter plot matrix with univariate boxplots on the main
## diagonal.
X <- iris[,1:4]
group <- iris[,5]
spmplot(X, group, variables=c('SL','SW','PL','PW'), dispopt="box")
## Example of spmplot() called by routine fsmult().
## Generate contaminated data.
n <- 200; p <- 3
X <- matrix(rnorm(n*p), ncol=3)
Xcont <- X
Xcont[1:5,] <- Xcont[1:5,] + 3
## spmplot is called automatically by all outlier detection methods, e.g. fsmult()
out <- fsmult(Xcont, plot=TRUE)
## Now test the direct use of fsmult(). Set two groups, e.g. those obtained
## from fsmult().
group = rep(0, n)
group[out$outliers] <- 1
## option 'labeladd' is used to label the outliers
## By default, the legend identifies the groups with the identifiers
## given in vector 'group'.
spmplot(Xcont, group, col=c("blue", "red"), labeladd=1, dispopt="box")
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