Package: BinaryEPPM
Type: Package
Title: Mean and Scale-Factor Modeling of Under- And Over-Dispersed
        Binary Data
Version: 3.0
Imports: Formula, expm, numDeriv, stats, lmtest, grDevices, graphics
Date: 2024-06-03
Authors@R: c(person(c("David", "M."), "Smith", role = c("aut", "cre"),
                    email = "dmccsmith@verizon.net"),
             person(c("Malcolm", "J."), "Faddy", role = "aut"))
Depends: R (>= 3.5.0)
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>.
License: GPL-2
Suggests: R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2024-06-03 18:18:25 UTC; dmccs
Author: David M. Smith [aut, cre],
  Malcolm J. Faddy [aut]
Maintainer: David M. Smith <dmccsmith@verizon.net>
Repository: CRAN
Date/Publication: 2024-06-04 10:32:25 UTC
Built: R 4.3.3; ; 2025-01-24 04:44:02 UTC; unix
