Morpho (version 2.1)

permuvec: perfom permutation testing on angles and distances between subgroups of two major groups.

Description

perform permutation test on length and angle of the vectors connecting the subgroup means of two groups: e.g. compare if length and angle between sex related differences in two populations differ significantly.

Usage

permuvec(data, groups, subgroups = NULL, rounds = 10000, scale = TRUE,
  tol = 1e-10, mc.cores = parallel::detectCores())

Arguments

data

array or matrix containing data.

groups

factors of firs two grouping variables.

subgroups

factors of the subgrouping.

rounds

number of requested permutation rounds

scale

if TRUE: data will be scaled by pooled within group covarivance matrix. Otherwise Euclidean distance will be used for calculating distances.

tol

threshold for inverting covariance matrix.

mc.cores

integer: determines how many cores to use for the computation. The default is autodetect. But in case, it doesn't work as expected cores can be set manually.Parallel processing is disabled on Windows due to occasional errors.

Value

• angle
  angle between the vectors of the subgroups means
• dist
  distances between subgroups
• meanvec
  matrix containing the means of all four subgroups
• permutangles
  vector containing angles (in radians) from random permutation
• permudists
  vector containing distances from random permutation
• p.angle
  p-value of angle between residual vectors
• p.dist
  p-value of length difference between residual vectors
• subdist
  length of residual vectors connecting the subgroups
• means.

Details

This function calculates means of all four subgroups and compares the residual vectors of the major grouping variables by angle and distance.

Examples

data(boneData)
proc <- procSym(boneLM)
pop <- name2factor(boneLM,which=3)
sex <- name2factor(boneLM,which=4)
## use non scaled distances by setting \\code{scale = FALSE}
## and only use first 10 PCs
perm <- permuvec(proc$PCscores[,1:10], groups=pop, subgroups=sex,
                 scale=FALSE, rounds=100, mc.cores=2)


## visualize if the amount of sexual dimorphism differs between
# (lenghts of vectors connecting population specific sex's averages)
# differs between European and Chines
hist(perm$permudist, xlim=c(0,0.1),main="measured vs. random distances",
     xlab="distances")
points(perm$dist,10,col=2,pch=19)#actual distance
text(perm$dist,15,label=paste("actual distance\n
     (p=",perm$p.dist,")"))
## not significant!!

## visualize if the direction of sexual dimorphism
# (angle between vectors connecting population specific sex's averages)
# differs between European and Chines
hist(perm$permutangles, main="measured vs. random angles",
     xlab="angles")
points(perm$angle,10,col=2,pch=19)#actual distance
text(perm$angle,15,label=paste("actual distance\n
    (p=",perm$p.angle,")"))
## also non-significant