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

Journal Article


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).

Publication Date


  • 2018

Citation


  • 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.

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/247

Number Of Pages


  • 19

Start Page


  • 1

End Page


  • 20

Volume


  • 86

Issue


  • Code Snippet 2

Place Of Publication


  • United States

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).

Publication Date


  • 2018

Citation


  • 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.

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/247

Number Of Pages


  • 19

Start Page


  • 1

End Page


  • 20

Volume


  • 86

Issue


  • Code Snippet 2

Place Of Publication


  • United States