rPLSIM: Simulation of non-normal data In covsim: VITA, IG and PLSIM Simulation for Given Covariance and Marginals

 rPLSIM R Documentation

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 (njal.foldnes@gmail.com)

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.