DAAG (version 0.37)

possum: Possum Measurements

Description

The possum data frame consists of nine morphometric measurements on each of 104 mountain brushtail possums, trapped at seven sites from Southern Victoria to central Queensland.

Usage

data(possum)

source

Lindenmayer, D. B., Viggers, K. L., Cunningham, R. B., and Donnelly, C. F. 1995. Morphological variation among columns of the mountain brushtail possum, Trichosurus caninus Ogilby (Phalangeridae: Marsupiala). Australian Journal of Zoology 43: 449-458.

Examples

data(possum)
boxplot(earconch~sex, data=possum)
pause()

sex <- as.integer(possum$sex)
pairs(possum[, c(9:11)], oma=c(2,4,5,4), pch=c(0,2:7), col=c("red","blue"),
  labels=c("tail
length","foot
length","ear conch
length"))
chh <- par()$cxy[2]; xleg <- 0.05; yleg <- 1.04
oldpar <- par(xpd=TRUE)  
legend(xleg, yleg, c("Cambarville", "Bellbird", "Whian Whian  ",
  "Byrangery", "Conondale  ","Allyn River", "Bulburin"), pch=c(0,2:7),
  x.intersp=1, y.intersp=0.75, cex=0.8, xjust=0, bty="n", ncol=4)
text(x=0.2, y=yleg - 2.25*chh, "female", col="red", cex=0.8, bty="n")
text(x=0.75, y=yleg - 2.25*chh, "male", col="blue", cex=0.8, bty="n")
par(oldpar)
pause()

sapply(possum[,6:14], function(x)max(x,na.rm=TRUE)/min(x,na.rm=TRUE))
pause()

require(mva)           # Load multivariate analysis library
here <- na.omit(possum$footlgth)
possum.prc <- princomp(possum[here, 6:14])
pause()

plot(possum.prc$scores[,1] ~ possum.prc$scores[,2],
  col=c("red","blue")[as.numeric(possum$sex[here])],
  pch=c(0,2:7)[possum$site[here]], xlab = "PC1", ylab = "PC2")
  # NB: We have abbreviated the axis titles
chh <- par()$cxy[2]; xleg <- -15; yleg <- 20.5
oldpar <- par(xpd=TRUE)
legend(xleg, yleg, c("Cambarville", "Bellbird", "Whian Whian  ",
  "Byrangery", "Conondale  ","Allyn River", "Bulburin"), pch=c(0,2:7),
  x.intersp=1, y.intersp=0.75, cex=0.8, xjust=0, bty="n", ncol=4)
text(x=-9, y=yleg - 2.25*chh, "female", col="red", cex=0.8, bty="n")
summary(possum.prc, loadings=TRUE, digits=2)
par(oldpar)
pause()

require(MASS)
here <- !is.na(possum$footlgth)
possum.lda <- lda(site ~ hdlngth+skullw+totlngth+ taill+footlgth+
  earconch+eye+chest+belly, data=possum, subset=here)
options(digits=4)
possum.lda$svd   # Examine the singular values   
plot(possum.lda, dimen=3)
  # Scatterplot matrix - scores on 1st 3 canonical variates (Figure 11.4)
possum.lda