possum | R Documentation |
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.
data(possum)
data(fossum)
This data frame contains the following columns:
observation number
one of seven locations where possums were trapped. The sites were, in order,Cambarville, Bellbird, Whian Whian, Byrangery, Conondale, Allyn River and Bulburin
a factor which classifies the sites as Vic
Victoria,
other
New South Wales or Queensland
a factor with levels
f
female,
m
male
age
head length
skull width
total length
tail length
foot length
ear conch length
distance from medial canthus to lateral canthus of right eye
chest girth (in cm)
belly girth (in cm)
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.
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)
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