ordcont) sets up the gaussian 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.This version has fixed some drawbacks in terminology in the previous version; the only actual change concerns the parameter cormat in the ordsample function. Further examples of implementation have been added.
| Package: |
| GenOrd |
| Type: |
| Package |
| Version: |
| 1.4.0 |
| Date: |
| 2015-09-11 |
| License: |
| GPL |
| LazyLoad: |
| yes |
A. Barbiero, P.A. Ferrari (2014) Simulation of correlated Poisson variables. Applied Stochastic Models in Business and Industry, doi 10.1002/asmb.2072
contord, ordcont, corrcheck, ordsample