Learn R Programming

Morpho (version 2.1)

CAC: calculate common allometric component

Description

calculate common allometric component

Usage

CAC(x, size, groups = NULL, log = FALSE)

Arguments

x
datamatrix (e.g. with PC-scores) or 3D-array with landmark coordinates
size
vector with Centroid sizes
groups
grouping variable
log
logical: use log(size)

Value

  • CACscorescommon allometric component scores
  • CACcommon allometric component
  • x(group-) centered data
  • scCAC reprojected into original space by applying CAC %*% x
  • RSCscoresresidual shape component scores
  • RSCresidual shape components
  • gmeansgroupmeans
  • CSthe centroid sizes (log transformed if log = TRUE)

References

Mitteroecker P, Gunz P, Bernhard M, Schaefer K, Bookstein FL. 2004. Comparison of cranial ontogenetic trajectories among great apes and humans. Journal of Human Evolution 46(6):679-97.

Examples

Run this code
data(boneData)
proc <- procSym(boneLM)
pop.sex <- name2factor(boneLM,which=3:4)
cac <- CAC(proc$rotated,proc$size,pop.sex)
plot(cac$CACscores,cac$size)#plot scores against Centroid size
cor.test(cac$CACscores,cac$size)#check for correlation
#visualize differences between large and small on the sample's consensus
large <- showPC(max(cac$CACscores),cac$CAC,proc$mshape)
small <- showPC(min(cac$CACscores),cac$CAC,proc$mshape)
deformGrid3d(small,large,ngrid=0)

Run the code above in your browser using DataLab