rVM: Simulation of non-normal data with the Vale-Maurelli method

In covsim: VITA, IG, PLSIM and VM Simulation for Given Covariance and Marginals

Simulation of non-normal data with the Vale-Maurelli method

Description

Convenience wrapper that combines calibrate_vm and simulate in one call. Prefer the calibrate/simulate split when drawing many samples from the same target.

Usage

rVM(N, sigma.target, skewness, excesskurtosis, reps = 1)

Arguments

N	Number of observations to simulate.
sigma.target	Target population covariance matrix.
skewness	Target skewness vector.
excesskurtosis	Target excess kurtosis vector.
reps	Number of simulated samples.

Value

A list of simulated samples.

References

Vale, C. D. and Maurelli, V. A. (1983). Simulating multivariate nonnormal distributions. Psychometrika, 48(3), 465-471.

Examples

sigma.target <- matrix(c(1, 0.5, 0.5, 1), 2)
my.samples <- rVM(N = 1000, sigma.target, skewness = c(1, 2),
                  excesskurtosis = c(2, 7), reps = 5)

covsim documentation built on Oct. 29, 2026, 5:06 p.m.