Compare matrices via the correlation between response vectors
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, ...) ## Default S3 method: DeltaZCorr(cov.x, cov.y, skewers, ...) ## S3 method for class 'list' DeltaZCorr(cov.x, cov.y = NULL, skewers, parallel = FALSE, ...)
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. |
skewers |
matrix of column vectors to be used as gradients |
... |
aditional arguments passed to other methods. |
parallel |
if TRUE computations are done in parallel. Some foreach backend must be registered, like doParallel or doMC. |
vector of vector correlations between the expected responses for the two matrices for each supplied vector
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.
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)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.