Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
mipfp: An R Package for Multidimensional Array Fitting and Simulating Multivariate Bernoulli Distributions | Barthélemy | Journal of Statistical Software
Authors: Johan Barthélemy, Thomas Suesse
Title: mipfp: An R Package for Multidimensional Array Fitting and Simulating Multivariate Bernoulli Distributions
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).

Page views:: 295. Submitted: 2015-09-27. Published: 2018-09-03.
Paper: mipfp: An R Package for Multidimensional Array Fitting and Simulating Multivariate Bernoulli Distributions     Download PDF (Downloads: 87)
Supplements:
mipfp_3.2.1.tar.gz: R source package Download (Downloads: 5; 161KB)
v86c02.R: R replication code Download (Downloads: 4; 3KB)

DOI: 10.18637/jss.v086.c02

by
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.