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BinaryEPPM

Mean and Scale-Factor Modeling of Under- And Over-Dispersed Binary Data

v3.0 · Jun 4, 2024 · GPL-2

Description

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>.

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies Formula expm numDeriv lmtest BinaryEPPM

Version History

new 3.0 Mar 10, 2026
updated 3.0 ← 2.3 diff Jun 3, 2024
updated 2.3 ← 2.2 diff Jul 30, 2019
updated 2.2 ← 2.1 diff Apr 30, 2018
updated 2.1 ← 2.0 diff Nov 22, 2017
updated 2.0 ← 1.0 diff Nov 27, 2016
new 1.0 May 13, 2015