permuvec | R Documentation |
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.
permuvec(
data,
groups,
subgroups = NULL,
rounds = 9999,
scale = TRUE,
tol = 1e-10,
mc.cores = parallel::detectCores()
)
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. |
This function calculates means of all four subgroups and compares the residual vectors of the major grouping variables by angle and distance.
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.
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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.