calibrate_plsim: Calibrate the PLSIM (Piecewise Linear) model

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

Calibrate the PLSIM (Piecewise Linear) model

Description

Performs the calibration step of the PLSIM algorithm: fits piecewise linear marginal transforms with the target skewness and kurtosis and searches for intermediate normal correlations that yield the target covariance after transformation. The (expensive) pairwise calibration is decoupled from simulation so the resulting calibration object can be reused to draw many samples without recomputation.

Usage

calibrate_plsim(
  sigma.target,
  skewness,
  excesskurtosis,
  numsegments = 4,
  gammalist = NULL,
  monot = FALSE,
  verbose = TRUE
)

Arguments

sigma.target	Target population covariance matrix.
skewness	Target skewness vector.
excesskurtosis	Target excess kurtosis vector.
numsegments	The number of line segments in each marginal.
gammalist	A list of breakpoints in each margin.
monot	If TRUE, piecewise linear functions are forced to be monotonous. The implied copula is then normal.
verbose	If TRUE, prints calibration progress.

Value

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

Author(s)

Njål Foldnes ([e-mail])

References

Foldnes, N. and Grønneberg S. (2021). Non-normal data simulation using piecewise linear transforms.

See Also

rPLSIM, simulate

Examples

set.seed(1)
sigma.target <- cov(MASS::mvrnorm(5, rep(0, 3), diag(3)))
cal <- calibrate_plsim(sigma.target, skewness = rep(1, 3), excesskurtosis = rep(4, 3))
samples <- stats::simulate(cal, nsim = 2, N = 1000)

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