RM_norm: Generate a normal random matrix

In RMAT: Random Matrix Analysis Toolkit

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)

RMAT documentation built on April 28, 2021, 9:06 a.m.