VITA, IG and PLSIM Simulation for Given Covariance and Marginals
c(person("Njaal", "Foldnes", email = "njal.foldnes@gmail.com", role = c("aut", "cre")),
person("Steffen", "Groenneberg", email = "steffeng@gmail.com", role = c("aut")))
User specifies population covariance matrix. Marginal information may be fully
specified, for which the package implements the VITA (VIne-To-Anything) algorithm.
Groenneberg and Foldnes (2017) <doi:10.1007/s11336-017-9569-6>.
Alternatively, marginal skewness and kurtosis may be specified, for which the package
implements the IG (independent generator) and PLSIM (piecewise linear) algorithms. Foldnes and Olsson (2016) <doi:10.1080/00273171.2015.1133274>.
Foldnes and Groenneberg (2021).
rvinecopulib (>= 0.5.1.1.0), lavaan (>= 0.6-5), nleqslv,
PearsonDS, MASS, stats, Rcpp, gsl, tmvtnorm, Matrix
Njaal Foldnes [aut, cre],
Steffen Groenneberg [aut]

c(person("Njaal", "Foldnes", email = "njal.foldnes@gmail.com", role = c("aut", "cre")),
person("Steffen", "Grønneberg", email = "steffeng@gmail.com", role = c("aut")))
Random sampling from distributions with user-specified population covariance matrix. Marginal information may be fully
specified, for which the package implements the VITA (VIne-To-Anything) algorithm
Grønneberg and Foldnes (2017) <doi:10.1007/s11336-017-9569-6>.  See also Grønneberg, Foldnes and Marcoulides (2022) <doi:10.18637/jss.v102.i03>.
Alternatively, marginal skewness and kurtosis may be specified, for which the package
implements the IG (independent generator) and PLSIM (piecewise linear) algorithms, see Foldnes and Olsson (2016) <doi:10.1080/00273171.2015.1133274> and
Foldnes and Grønneberg (2021) <doi:10.1080/10705511.2021.1949323>, respectively.
Njaal Foldnes [aut, cre],
Steffen Grønneberg [aut]

Performs Segmented Linear Regression on Two Independent
Variables
person("Christoph", "Luerig", email = "luerig@hochschule-trier.de", role=c("aut", "cre"))
Implements a specific form of segmented linear regression
with two independent variables. The visualization of that function looks
like a quarter segment of a cowbell giving the package its name.
The package has been specifically constructed for the case where minimum
and maximum value of the dependent and two independent variables
are known a prior, which is usually the case
when those values are derived from Likert scales.