The R Journal: article published in 2019, volume 11:1

SimCorrMix: Simulation of Correlated Data with Multiple Variable Types Including Continuous and Count Mixture Distributions PDF download
Allison Fialkowski and Hemant Tiwari , The R Journal (2019) 11:1, pages 250-286.

Abstract The SimCorrMix package generates correlated continuous (normal, non-normal, and mix ture), binary, ordinal, and count (regular and zero-inflated, Poisson and Negative Binomial) variables that mimic real-world data sets. Continuous variables are simulated using either Fleishman’s third order or Headrick’s fifth-order power method transformation. Simulation occurs at the component level for continuous mixture distributions, and the target correlation matrix is specified in terms of correlations with components. However, the package contains functions to approximate expected correlations with continuous mixture variables. There are two simulation pathways which calculate intermediate correlations involving count variables differently, increasing accuracy under a wide range of parameters. The package also provides functions to calculate cumulants of continuous mixture distributions, check parameter inputs, calculate feasible correlation boundaries, and summarize and plot simulated variables. SimCorrMix is an important addition to existing R simulation packages because it is the first to include continuous mixture and zero-inflated count variables in correlated data sets.

Received: 2018-04-04; online 2019-08-16, supplementary material, (5.3 KiB)
CRAN packages: AdaptGauss, DPP, bgmm, ClusterR, mclust, mixture, AdMit, bimixt, bmixture, CAMAN, flexmix, mixdist, mixtools, nspmix, MixtureInf, Rmixmod, hurdlr, zic, mixpack, distr, stats, rebmix, SimCorrMix, SimMultiCorrData, GenOrd, VGAM, Matrix, ggplot2, mvtnorm
CRAN Task Views implied by cited CRAN packages: Cluster, Distributions, Multivariate, Bayesian, Environmetrics, Econometrics, Psychometrics, ExtremeValue, Finance, Graphics, MetaAnalysis, NumericalMathematics, Phylogenetics, Robust, SocialSciences, Survival, TeachingStatistics

CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

  author = {Allison Fialkowski and Hemant Tiwari},
  title = {{SimCorrMix: Simulation of Correlated Data with Multiple
          Variable Types Including Continuous and Count Mixture
  year = {2019},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2019-022},
  url = {},
  pages = {250--286},
  volume = {11},
  number = {1}