RandomSkewers: Compare matrices via RandomSkewers

Description

Calculates covariance matrix correlation via random skewers

Usage

RandomSkewers(cov.x, cov.y, ...)
## S3 method for class 'default':
RandomSkewers(cov.x, cov.y, num.vectors = 1000, ...)
## S3 method for class 'list':
RandomSkewers(cov.x, cov.y = NULL, num.vectors = 1000,
  repeat.vector = NULL, parallel = FALSE, ...)

Arguments

cov.x

Single covariance matrix or list of covariance matrices. If single matrix is suplied, it is compared to cov.y. If list is suplied and no cov.y is suplied, all matrices are compared. If cov.y is suplied, all matrices in list are compared to it.

cov.y

First argument is compared to cov.y. Optional if cov.x is a list.

...

aditional arguments passed to other methods.

num.vectors

Number of random vectors used in comparison.

repeat.vector

Vector of repeatabilities for correlation correction.

parallel

if TRUE computations are done in parallel. Some foreach backend must be registered, like doParallel or doMC.

Value

If cov.x and cov.y are passed, returns average value of response vectors correlation ('correlation'), significance ('probability') and standard deviation of response vectors correlation ('correlation_sd')
If cov.x and cov.y are passed, same as above, but for all matrices in cov.x.
If only a list is passed to cov.x, a matrix of RandomSkewers average values and probabilities of all comparisons. If repeat.vector is passed, comparison matrix is corrected above diagonal and repeatabilities returned in diagonal.

References

Cheverud, J. M., and Marroig, G. (2007). Comparing covariance matrices: Random skewers method compared to the common principal components model. Genetics and Molecular Biology, 30, 461-469.

Examples

Run this code

c1 <- RandomMatrix(10)
c2 <- RandomMatrix(10)
c3 <- RandomMatrix(10)
RandomSkewers(c1, c2)

RandomSkewers(list(c1, c2, c3))

reps <- unlist(lapply(list(c1, c2, c3), MonteCarloRep, sample.size = 10,
                                        RandomSkewers, num.vectors = 100,
                                        iterations = 10))
RandomSkewers(list(c1, c2, c3), repeat.vector = reps)

c4 <- RandomMatrix(10)
RandomSkewers(list(c1, c2, c3), c4)

#Multiple threads can be used with some foreach backend library, like doMC or doParallel
#library(doParallel)
##Windows:
#cl <- makeCluster(2)
#registerDoParallel(cl)
##Mac and Linux:
#registerDoParallel(cores = 2)
#RandomSkewers(list(c1, c2, c3), parallel = TRUE)