RM_norm {RMAT} | R Documentation |
Generate a normal random matrix
Description
Normal random matrices are matrices with normally distributed entries. These matrices are extensively studied in random matrix theory.
Usage
RM_norm(N, mean = 0, sd = 1, symm = FALSE, cplx = FALSE, herm = FALSE)
Arguments
N |
number of dimensions of the square matrix |
mean |
mean of the normal distribution of entries |
sd |
standard deviation of the normal distribution of entries |
symm |
indicates whether the matrix should be symmetric (equal to its transpose). Reserved for when cplx = FALSE, otherwise use herm = TRUE. |
cplx |
indicates whether the matrix should have complex entries. |
herm |
indicates whether the matrix should be hermitian (equal to its conjugate transpose). Reserved for when cplx = TRUE, otherwise use symm = TRUE. |
Value
A random matrix with normally distributed entries.
Examples
# N(1,2) distributed matrix
P <- RM_norm(N = 3, mean = 1, sd = 2)
# N(0,5) distributed matrix with real symmetric entries
P <- RM_norm(N = 7, sd = 5, symm = TRUE)
# 7x7 standard normal matrix with complex entries
Q <- RM_norm(N = 7, cplx = TRUE)
# N(2,1) distributed matrix with hermitian complex entries
Q <- RM_norm(N = 5, mean = 2, cplx = TRUE, herm = TRUE)
[Package RMAT version 0.2.0 Index]