The package implements a procedure for generating samples from a multivariate discrete random variable with pre-specified correlation matrix and marginal distributions. The marginal distributions are linked together through either a Gaussian or a Student's t copula.
The procedure is developed in two steps: the first step (function ordcont) sets up the Gaussian/t copula in order to achieve the desired correlation matrix on the target random discrete components; the second step (ordsample) generates samples from the target variables.
The procedure can handle both Pearson's and Spearman's correlations, and any finite support for the discrete variables.
The intermediate function contord computes the correlations of the multivariate discrete variable derived from correlated normal variables through discretization.
Function corrcheck returns the lower and upper bounds of the correlation coefficient of each pair of discrete variables given their marginal distributions, i.e., returns the range of feasible bivariate correlations.
Function estcontord, to be used with bivariate samples only, estimates the parameters of the Gaussian/t copula and possibly of the margins.
Compared to version 1.4.0, this version has introduced the multivariate Student's t copula as an alternative latent structure
Alessandro Barbiero, Pier Alda Ferrari
Maintainer: Alessandro Barbiero <alessandro.barbiero@unimi.it>
| Package: | GenOrd |
| Type: | Package |
| Version: | 2.0.0 |
| Date: | 2025-08-11 |
| License: | GPL |
| LazyLoad: | yes |
P.A. Ferrari, A. Barbiero (2012) Simulating ordinal data, Multivariate Behavioral Research, 47(4), 566-589
A. Barbiero, P.A. Ferrari (2015) Simulation of correlated Poisson variables. Applied Stochastic Models in Business and Industry, 31(5), 669-680.
A. Barbiero, P.A. Ferrari (2017) An R package for the simulation of correlated discrete variables. Communications in Statistics-Simulation and Computation, 46(7), 5123-5140.
contord, ordcont, corrcheck, ordsample, estcontord