A package for the stochastic simulation of discrete variables with assigned marginal distributions and correlation matrix is presented and discussed. The simulating mechanism relies upon the Gaussian copula, linking the discrete distributions together, and an iterative scheme recovering the correlation matrix for the copula that ensures the desired correlations among the discrete variables. Examples of its use are provided as well as three possible applications (related to probability, sampling, and inference), which illustrate the utility of the package as an efficient and easy-to-use tool both in statistical research and for didactic purposes.

An R package for the simulation of correlated discrete variables / A. Barbiero, P.A. Ferrari. - In: COMMUNICATIONS IN STATISTICS. SIMULATION AND COMPUTATION. - ISSN 0361-0918. - (2016 Mar 07), pp. 1-18. [Epub ahead of print]

An R package for the simulation of correlated discrete variables

A. Barbiero
;
P.A. Ferrari
Ultimo
2016-03-07

Abstract

A package for the stochastic simulation of discrete variables with assigned marginal distributions and correlation matrix is presented and discussed. The simulating mechanism relies upon the Gaussian copula, linking the discrete distributions together, and an iterative scheme recovering the correlation matrix for the copula that ensures the desired correlations among the discrete variables. Examples of its use are provided as well as three possible applications (related to probability, sampling, and inference), which illustrate the utility of the package as an efficient and easy-to-use tool both in statistical research and for didactic purposes.
Correlation matrix; Gaussian copula; Multivariate discrete distribution; Statistics and Probability; Modeling and Simulation
Settore SECS-S/01 - Statistica
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/501194
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