Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: David M. Smith, Malcolm J. Faddy
Title: Mean and Variance Modeling of Under-Dispersed and Over-Dispersed Grouped Binary Data
Abstract: This article describes the R package BinaryEPPM and its use in determining maximum likelihood estimates of the parameters of extended Poisson process models for grouped binary data. These provide a Poisson process family of flexible models that can handle unlimited under-dispersion but limited over-dispersion in such data, with the binomial distribution being a special case. Within BinaryEPPM, models with the mean and variance related to covariates are constructed to match a generalized linear model formulation. Combining such under-dispersed models with standard over-dispersed models such as the beta binomial distribution provides a very general form of residual distribution for modeling grouped binary data. Use of the package is illustrated by application to several data-sets.

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Paper: Mean and Variance Modeling of Under-Dispersed and Over-Dispersed Grouped Binary Data     Download PDF (Downloads: 122)
Supplements:
BinaryEPPM_2.3.tar.gz: R source package Download (Downloads: 5; 117KB)
v90i08.R: R replication code Download (Downloads: 7; 10KB)
v90i08-supplemental-examples.R: R replication code Download (Downloads: 6; 19KB)

DOI: 10.18637/jss.v090.i08

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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.