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Generate Correlation Matrix from Random Samples.

Source: R/cormat.R
cor_matrix.Rd

This function generates random samples from specified probability distributions and computes the correlation matrix for the generated samples.

Usage

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

Arguments

num_samples

The number of samples to generate.

num_vars

The number of distributions to sample.

dists

A list describing each distribution. Each element should be a function that generates random samples. The names of the list elements will be used to identify the distributions.

Value

The function returns the correlation matrix for the distributions.

References

Govan, Paul, and Ivan Damnjanovic. "The resource-based view on project risk management." Journal of construction engineering and management 142.9 (2016): 04016034.

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,]  1.00000000 -0.03690034 -0.07459820  0.16084884 -0.06662177
#> [2,] -0.03690034  1.00000000 -0.01642801 -0.10972562 -0.02762785
#> [3,] -0.07459820 -0.01642801  1.00000000 -0.09137076 -0.14507929
#> [4,]  0.16084884 -0.10972562 -0.09137076  1.00000000 -0.11794046
#> [5,] -0.06662177 -0.02762785 -0.14507929 -0.11794046  1.00000000