Mixed data generation packages and related computational tools in R

Abstract

This paper is concerned with providing some computation-related details of the 16R packages that have been developed by Demirtas and his colleagues in the context of random number generation. The dominant theme is multivariate mixed data generation. However, univariate and multivariate data generation from different distributions as well as some other tools such as modeling the correlation transitions in latency and discretization domains are also included. This is intended for interested people who would benefit from access to a comprehensive set of data simulation tools at one single place. While the focus is on conceptual and implementation issues, the ideas are supported by appropriate references for methodological development.

Keywords:

• Univariate
• multivariate
• mixed data
• stochastic simulation
• random number generation