Generate a data frame with a predetermined correlation structure

Simulates multivariate normal data whose columns reproduce a target correlation matrix, using Cholesky decomposition. If no matrix is supplied, a random symmetric positive-definite matrix is generated automatically.

Usage

generate_correlation_matrix(correlation_martix, nrows = 10)

Arguments

correlation_martix

A symmetric positive-definite matrix specifying the desired correlations between columns. Must pass Cholesky decomposition. If omitted, a random correlation matrix is generated.

nrows

Integer. Number of observations (rows) to generate. Default is 10.

Value

A data frame with nrows rows and ncol(correlation_martix) columns of simulated numeric values.

Details

Uses Cholesky decomposition (chol()) to factor the target correlation matrix, then multiplies by independent standard normal draws to produce correlated columns. The resulting correlations approximate the target matrix, with accuracy improving as nrows increases.

See also

generate_data, symmetric_matrix

Examples

df <- data.frame(matrix(.999, ncol = 2, nrow = 2))
correlation_martix <- as.matrix(df)
diag(correlation_martix) <- 1
df <- generate_correlation_matrix(correlation_martix, nrows = 100)
stats::cor(df)
#>        X1     X2
#> X1 1.0000 0.9989
#> X2 0.9989 1.0000