Generate Correlation Matrix.

Usage

cor_matrix(num_samples = 100, num_vars = 5, dists = dists)

Arguments

num_samples: The number of samples to generate.
num_vars: The number of distributions to sample.
dists: A list describing each distribution.

Value

The function returns the correlation matrix for the distributions.

Examples

# List of probability distributions
dists <- list(
  normal = function(n) rnorm(n, mean = 0, sd = 1),
  uniform = function(n) runif(n, min = 0, max = 1),
  exponential = function(n) rexp(n, rate = 1),
  poisson = function(n) rpois(n, lambda = 1),
  binomial = function(n) rbinom(n, size = 10, prob = 0.5)
)

# Generate correlation matrix
cor_matrix <- cor_matrix(num_samples = 100, num_vars = 5, dists = dists)

# Print correlation matrix
print(cor_matrix)
#>               [,1]        [,2]        [,3]         [,4]          [,5]
#> [1,]  1.000000e+00  0.16574655  0.07203118 -0.006606531  7.107618e-05
#> [2,]  1.657465e-01  1.00000000  0.12033562 -0.027319417  1.756293e-02
#> [3,]  7.203118e-02  0.12033562  1.00000000 -0.162796530 -1.028019e-02
#> [4,] -6.606531e-03 -0.02731942 -0.16279653  1.000000000 -1.483971e-01
#> [5,]  7.107618e-05  0.01756293 -0.01028019 -0.148397087  1.000000e+00