rcovmat {cds} | R Documentation |
Construct a low-rank covariance matrix with specified eigenvalues, where the eigenvectors are simulated from uniform distributions.
rcovmat(eigs = k:1, m = 10, k = 2, perc = list(c(0.4, 0.2, 0.4), c(0.2, 0.4, 0.4)), limits = list(l1 = c(0.5, 1), l2 = c(-1, -0.5), l3 = c(-0.1, 0.1)), random = TRUE)
eigs |
Vector of $k$ eigenvalues. |
m |
Integer; the number of rows and columns of the matrix. |
k |
Integer; the rank of the matrix. |
perc |
List of $k$ vectors giving the sampling proportions for the uniform sampling of the eigenvectors, for each dimension. |
limits |
List of length 2 vectors, one for each uniform sample, giving the lower and upper bounds of the uniform distribution. |
random |
Logical; randomize the order of the loading per dimension or not. |