@article{JSSv086c02, title={mipfp: An R Package for Multidimensional Array Fitting and Simulating Multivariate Bernoulli Distributions}, volume={86}, url={https://www.jstatsoft.org/index.php/jss/article/view/v086c02}, doi={10.18637/jss.v086.c02}, 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).}, number={2}, journal={Journal of Statistical Software, Code Snippets}, author={Barthélemy, Johan and Suesse, Thomas}, year={2018}, pages={1–20} }