# multivariate data with outliers
library(mvtnorm)
x <- rbind(rmvnorm(200, rep(0, 6), diag(c(5, rep(1,5)))),
rmvnorm( 15, c(0, rep(20, 5)), diag(rep(1, 6))))
# Here we calculate the principal components with PCAgrid
pc <- PcaGrid(x, 6)
# we could draw a biplot too:
biplot(pc)
# we could use another objective function, and
# maybe only calculate the first three principal components:
pc <- PcaGrid(x, 3, method="qn")
biplot(pc)
# now we want to compare the results with the non-robust principal components
pc <- PcaClassic(x, k=3)
# again, a biplot for comparision:
biplot(pc)
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