Possum Measurements

Description

The possum data frame consists of nine morphometric measurements on each of 104 mountain brushtail possums, trapped at seven Australian sites from Southern Victoria to central Queensland. See possumsites for further details. The fossum data frame is the subset of possum that has measurements for the 43 females.

Usage

  data(possum)
  data(fossum)
  

Format

This data frame contains the following columns:

case

observation number

site

one of seven locations where possums were trapped. The sites were, in order,Cambarville, Bellbird, Whian Whian, Byrangery, Conondale, Allyn River and Bulburin

Pop

a factor which classifies the sites as Vic Victoria, other New South Wales or Queensland

sex

a factor with levels f female, m male

age

age

hdlngth

head length

skullw

skull width

totlngth

total length

taill

tail length

footlgth

foot length

earconch

ear conch length

eye

distance from medial canthus to lateral canthus of right eye

chest

chest girth (in cm)

belly

belly girth (in cm)

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

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

sex <- as.integer(possum$sex)
oldpar <- par(oma=c(2,4,5,4))
pairs(possum[, c(9:11)], pch=c(0,2:7), col=c("red","blue"),
  labels=c("tail\nlength","foot\nlength","ear conch\nlength"))
chh <- par()$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()

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
pause()
boxplot(fossum$totlngth)