
Compares the expected response to selection for two matrices for a specific set of selection gradients (not random gradients like in the RandomSkewers method)
DeltaZCorr(cov.x, cov.y, skewers, ...)# S3 method for default
DeltaZCorr(cov.x, cov.y, skewers, ...)
# S3 method for list
DeltaZCorr(cov.x, cov.y = NULL, skewers, parallel = FALSE, ...)
vector of vector correlations between the expected responses for the two matrices for each supplied vector
Single covariance matrix or list of covariance matrices. If single matrix is supplied, it is compared to cov.y. If list is supplied and no cov.y is supplied, all matrices are compared. If cov.y is supplied, all matrices in list are compared to it.
First argument is compared to cov.y. Optional if cov.x is a list.
matrix of column vectors to be used as gradients
additional arguments passed to other methods.
if TRUE computations are done in parallel. Some foreach back-end must be registered, like doParallel or doMC.
Diogo Melo, Guilherme Garcia
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.
KrzCor
,MantelCor
,,RandomSkewers
x <- RandomMatrix(10, 1, 1, 10)
y <- RandomMatrix(10, 1, 1, 10)
n_skewers = 10
skewers = matrix(rnorm(10*n_skewers), 10, n_skewers)
DeltaZCorr(x, y, skewers)
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