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Under- and over-dispersed binary data are modeled using an extended Poisson process model (EPPM) appropriate for binary data. A feature of the model is that the under-dispersion relative to the binomial distribution only needs to be greater than zero, but the over-dispersion is restricted compared to other distributional models such as the beta and correlated binomials. Because of this, the examples focus on under-dispersed data and how, in combination with the beta or correlated distributions, flexible models can be fitted to data displaying both under- and over-dispersion. Using Generalized Linear Model (GLM) terminology, the functions utilize linear predictors for the probability of success and scale-factor with various link functions for p, and log link for scale-factor, to fit a variety of models relevant to areas such as bioassay. Details of the EPPM are in Faddy and Smith (2012) <doi:10.1002/bimj.201100214> and Smith and Faddy (2019) <doi:10.18637/jss.v090.i08>.
| Version: | 3.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Formula, expm, numDeriv, stats, lmtest, grDevices, graphics |
| Suggests: | R.rsp |
| Published: | 2024-06-04 |
| DOI: | 10.32614/CRAN.package.BinaryEPPM |
| Author: | David M. Smith [aut, cre], Malcolm J. Faddy [aut] |
| Maintainer: | David M. Smith <dmccsmith at verizon.net> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Citation: | BinaryEPPM citation info |
| CRAN checks: | BinaryEPPM results |
| Reference manual: | BinaryEPPM.pdf |
| Vignettes: |
Mean and Scale-Factor Modeling of Under- and Overdispersed Grouped Binary Data |
| Package source: | BinaryEPPM_3.0.tar.gz |
| Windows binaries: | r-devel: BinaryEPPM_3.0.zip, r-release: BinaryEPPM_3.0.zip, r-oldrel: BinaryEPPM_3.0.zip |
| macOS binaries: | r-release (arm64): BinaryEPPM_3.0.tgz, r-oldrel (arm64): BinaryEPPM_3.0.tgz, r-release (x86_64): BinaryEPPM_3.0.tgz, r-oldrel (x86_64): BinaryEPPM_3.0.tgz |
| Old sources: | BinaryEPPM archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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