Description Usage Format Details Source References Examples
Skull morphometric data on Rocky Mountain and Arctic wolves (Canis Lupus L.) taken from Morrison (1990), originally from Jolicoeur (1959).
1 |
A data frame with 25 observations on the following 11 variables.
group
a factor with levels ar:f
ar:m
rm:f
rm:m
,
comprising the combinations of location
and sex
location
a factor with levels ar
=Artic, rm
=Rocky Mountain
sex
a factor with levels f
=female, m
=male
x1
palatal length, a numeric vector
x2
postpalatal length, a numeric vector
x3
zygomatic width, a numeric vector
x4
palatal width outside first upper molars, a numeric vector
x5
palatal width inside second upper molars, a numeric vector
x6
postglenoid foramina width, a numeric vector
x7
interorbital width, a numeric vector
x8
braincase width, a numeric vector
x9
crown length, a numeric vector
All variables are expressed in millimeters.
The goal was to determine how geographic and sex differences among the wolf
populations are determined by these skull measurements.
For MANOVA or (canonical) discriminant analysis, the factors group
or location
and sex
provide alternative
parameterizations.
Morrison, D. F. Multivariate Statistical Methods, (3rd ed.), 1990. New York: McGraw-Hill, p. 288-289.
Jolicoeur, P. “Multivariate geographical variation in the wolf Canis lupis L.”, Evolution, XIII, 283–299.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | data(Wolves)
# using group
wolf.mod <-lm(cbind(x1,x2,x3,x4,x5,x6,x7,x8,x9) ~ group, data=Wolves)
Anova(wolf.mod)
wolf.can <-candisc(wolf.mod)
plot(wolf.can)
heplot(wolf.can)
# using location, sex
wolf.mod2 <-lm(cbind(x1,x2,x3,x4,x5,x6,x7,x8,x9) ~ location*sex, data=Wolves)
Anova(wolf.mod2)
wolf.can2 <-candiscList(wolf.mod2)
plot(wolf.can2)
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