calibrate_ig: Calibrate the IG (Independent Generator) model

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

Calibrate the IG (Independent Generator) model

Description

Performs the calibration step of the IG algorithm: computes the transformation matrix A and fits a Pearson distribution to each independent generator such that samples drawn from the calibrated model match the target covariance, skewness, and excess kurtosis. Calibration is decoupled from simulation so the same calibration object can be reused to draw many samples without recomputation.

Usage

calibrate_ig(sigma.target, skewness, excesskurtosis, typeA = "triang")

Arguments

sigma.target	Target population covariance matrix.
skewness	Target skewness vector.
excesskurtosis	Target excess kurtosis vector.
typeA	Either "triang" (default, triangular Cholesky factor) or "symm" (symmetric square root).

Value

An object of class c("covsim_calib_ig", "covsim_calib") that can be passed to simulate to draw samples.

Author(s)

Njål Foldnes ([e-mail])

References

Foldnes, N. and Olson, U. H. (2016). A simple simulation technique for nonnormal data with prespecified skewness, kurtosis, and covariance matrix. Multivariate behavioral research, 51(2-3), 207-219

See Also

rIG, simulate

Examples

sigma.target <- diag(3)
cal <- calibrate_ig(sigma.target, skewness = rep(1, 3), excesskurtosis = rep(3, 3))
samples <- stats::simulate(cal, nsim = 5, N = 1000)

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