wordcount.grouped

<p>The data are the number of occurences of an article in five-word and ten-word samples from 
Macaulay's 'Essay on Milton' and G.K. Chesterton's essay 'About the workers'.</p>

datasets

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>.

David Smith

BinaryEPPM

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

wordcount.grouped function

<p>The format is:
List of 4
 $ author      : Factor w/ 2 levels " Macaulay"," Chesterton": 1 1 2 2
 $ fsize       : Factor w/ 2 levels "5","10": 1 2 1 2
 $ vsize       : num [1:4] 5 10 5 10
 $ number.words:List of 4
  ..$ : num [1:6] 45 49 6 0 0 0
  ..$ : num [1:11] 27 44 26 3 0 0 0 0 0 0 ...
  ..$ : num [1:6] 32 35 3 0 0 0
  ..$ : num [1:11] 14 38 16 2 0 0 0 0 0 0 ...</p>

wordcount.grouped: Number of occurences of an article in five-word and ten-word samples from two authors.

Description

Usage

Arguments

Format

References

Examples