mipfp: An R Package for Multidimensional Array Fitting and Simulating Multivariate Bernoulli Distributions

Authors

Johan Barthelemy, University of WollongongFollow
Thomas F. Suesse, University of WollongongFollow

RIS ID

129927

Publication Details

Barthelemy, J. & Suesse, T. (2018). mipfp: An R Package for Multidimensional Array Fitting and Simulating Multivariate Bernoulli Distributions. Journal of Statistical Software, 86 (Code Snippet 2), 1-20.

Abstract

This paper explains the mipfp package for R with the core functionality of updating an d-dimensional array with respect to given target marginal distributions, which in turn can be multi-dimensional. The implemented methods include the iterative proportional fitting procedure (IPFP), the maximum likelihood method, the minimum chi-square and least squares procedures. The package also provides an application of the IPFP to simulate data from a multivariate Bernoulli distribution. The functionalities of the package are illustrated through two practical examples: the update of a 3-dimensional contingency table to match the targets for a synthetic population and the estimation and simulation of the joint distribution of the binary attribute impaired pulmonary function as used by Qaqish, Zink, and Preisser (2012).