Nothing
##
## Diagnostic of iris representation with 'var.rd' parameter - 2d and 3d
##
oask <- devAskNewPage(dev.interactive(orNone=TRUE))
bp1 <- bpca(iris[-5],
var.rb=TRUE,
var.rd=TRUE,
limit=3)
plot(bp1,
var.factor=.3,
obj.names=FALSE,
obj.pch=c('+', '-', '*')[unclass(iris$Species)],
obj.col=c('red', 'green3', 'blue')[unclass(iris$Species)],
obj.cex=1)
bp1$var.rd
bp1$eigenvec
# Graphical diagnostic
plot(bpca(iris[-5],
d=3:4),
var.factor=.6,
obj.names=FALSE,
obj.pch=c('+', '-', '*')[unclass(iris$Species)],
obj.col=c('red', 'green3', 'blue')[unclass(iris$Species)],
obj.cex=1)
# Interpretation:
# Sepal.length followed by Petal.Width contains information in dimensions
# (PC3) - the PC3 is, essentially, a contrast among both) that wasn't fully
# contemplated by the biplot reduction (PC1 and PC2) .
# Therefore, between all variables, they have a "poor" representation by a 2d
# biplot.
bp2 <- bpca(iris[-5],
d=1:3,
var.rb=TRUE,
var.rd=TRUE,
limit=2)
plot(bp2,
obj.names=FALSE,
obj.pch=c('+', '-', '*')[unclass(iris$Species)],
obj.col=c('red', 'green3', 'blue')[unclass(iris$Species)],
obj.cex=1)
bp2$var.rd
bp2$eigenvec
round(bp2$var.rb,
2)
round(cor(iris[-5]),
2)
# Good representation of all variables with a 3d biplot!
devAskNewPage(oask)
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