rPLSIM: Simulation of non-normal data

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

Simulation of non-normal data

Description

Using the piecewise linear PLSIM method to simulate non-normal data

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
excesskurtosis	Target excess kurtosis
reps	Number of simulated samples
numsegments	The number of line segments in each marginal
gammalist	A list of breakpoints in each margin
monot	True if piecewise linear functions are forced to be monotonous. The copula will then be normal.
verbose	If true, progress details of the procedure are printed

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 June 22, 2024, 9:32 a.m.