rcov_mat: Generate a random covariance matrix

In NeymanPearsonFan1/tpca: A function for tailoring PCA to change detection

Description

Generates a random correlation matrix by R rcor_mat, then scales it to a covariance matrix by CRC, where C is a diagonal matrix of uniformly generated standard deviations in a specified range.

Usage

rcov_mat(d, k0 = d, range_sd = c(0.2, 5), ...)

Arguments

d	An integer specifying the dimension of the correlation matrix.
k0	An integer. d - k0 are the number of independent dimensions.
range_sd	A vector of length 2 specifying the lower and upper bound of the uniform distribution for generating standard deviations.
...	Other arguments to rcor_mat.

Value

A covariance matrix with an attribute 'which_dims_cor', indicating which dimensions that are the correlated ones.

NeymanPearsonFan1/tpca documentation built on June 6, 2019, 7:40 a.m.