rcovmat: Construct a Structured Covariance Matrix for Simulations

Description Usage Arguments

View source: R/rcovmat.R

Description

Construct a low-rank covariance matrix with specified eigenvalues, where the eigenvectors are simulated from uniform distributions.

Usage

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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)

Arguments

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.


cds documentation built on May 29, 2017, 6:52 p.m.