rPLSIM: Simulation of non-normal data

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

Simulation of non-normal data

Description

Backward-compatible wrapper that combines calibrate_plsim and simulate in one call. New code should prefer the calibrate/simulate split so the (expensive) pairwise calibration can be reused.

Usage

rPLSIM(
  N,
  sigma.target,
  skewness,
  excesskurtosis,
  reps = 1,
  numsegments = 4,
  gammalist = NULL,
  monot = FALSE,
  verbose = TRUE
)

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.
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

A list with two elements. First element: the list of simulated samples. Second element: the fitted piecewise linear functions and the intermediate correlations matrix.

Author(s)

Njål Foldnes ([e-mail])

References

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

Examples

set.seed(1)
sigma.target  <- cov(MASS::mvrnorm(5, rep(0,3), diag(3)))
res  <- covsim::rPLSIM(10^5, sigma.target, skewness=rep(1,3), excesskurtosis=rep(4,3))
my.sample  <- res[[1]][[1]]

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