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| 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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Page views:: 2127. Submitted: 2016-12-15. Published: 2019-07-31. |
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| Paper: |
Mean and Variance Modeling of Under-Dispersed and Over-Dispersed Grouped Binary Data
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| DOI: |
10.18637/jss.v090.i08
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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. |