generate_gaussian_copula_samples {covalchemy} | R Documentation |
Generate Gaussian Copula Samples
Description
This function generates samples from a Gaussian copula given a specified
correlation matrix. The samples are uniformly distributed in [0, 1]
across
dimensions.
Usage
generate_gaussian_copula_samples(n, d, rho_matrix)
Arguments
n |
Integer. The number of samples to generate. |
d |
Integer. The dimensionality of the copula. |
rho_matrix |
A |
Details
The function works as follows:
Generates multivariate normal samples with the given correlation matrix.
Transforms the samples to the uniform distribution
[0, 1]
using the cumulative distribution function (CDF) of the standard normal.
Value
A matrix of size n x d
, where each row represents a sample
and each column corresponds to a dimension. The values are uniformly
distributed in [0, 1]
.
Examples
# Example usage:
library(MASS) # Load package for `mvrnorm`
rho_matrix <- matrix(c(1, 0.5, 0.5, 1), nrow = 2) # 2x2 correlation matrix
samples <- generate_gaussian_copula_samples(n = 1000, d = 2, rho_matrix = rho_matrix)
head(samples)
[Package covalchemy version 1.0.0 Index]