BinaryEPPM (version 3.0)

Model.JMVGB: Probabilities for EPPM extended binomial distributions given p's and scale-factors.

Description

Calculates the probabilities for binomial and generalized binomial given values for p's and scale-factors.

Usage

Model.JMVGB(parameter, model.name, link, ntrials, 
            covariates.matrix.p, covariates.matrix.scalef, 
            offset.p = c(rep(0, length(ntrials))), 
            offset.scalef = c(rep(0, length(ntrials))))

Value

List of arguments input together with a list of probabilities vectors and a data frame of values of a and b of Equation (5) of Faddy and Smith (2012).

model

The model is either 'binomial' or 'EPPM extended binomial'.

link

The link is either 'logit' or 'cloglog'.

parameter

A vector of the parameters of the model which is set to initial estimates on function call.

probabilities

A list of the vectors of probabilities of the model.

Dparameters

A data frame of values of a and b of Equation (5) of Faddy and Smith (2012).

Arguments

parameter

A vector of the parameters of the model which is set to initial estimates on function call.

model.name

The model being fitted is one of the two 'binomial' or 'EPPM extended binomial'.

link

Takes one of nine values i.e., 'logit', 'probit', 'cloglog', 'cauchit', 'log', 'loglog', 'double exponential', 'double reciprocal', 'power logit'. The default is 'cloglog'. The 'power logit' has an attribute of 'power' for which the default is 1 i.e., a logit link.

ntrials

This is a scalar representing the denominator i.e., the length of the probability mass function returned is this scalar + 1.

covariates.matrix.p

A matrix of covariates for p where rows are the number of values in listbinary and columns the covariates. This matrix is extracted from the formulae in function BinaryEPPM. However, in the accompanying example it is shown how it can be constructed independently of function BinaryEPPM.

covariates.matrix.scalef

A matrix of covariates for the scale-factor where rows are the number of values in listbinary and columns the covariates. The default is a vector of ones. This matrix is extracted from the formulae in function BinaryEPPM. However, in the accompanying example it is shown how it can be constructed independently of function BinaryEPPM.

offset.p

An offset vector for p. The default is a vector of ones.

offset.scalef

An offset vector for the scale-factor. The default is a vector of ones.

Author

David M. Smith <[e-mail]>

References

Faddy M, Smith D. (2012). Extended Poisson Process Modeling and Analysis of Grouped Binary Data. Biometrical Journal, 54, 426-435. tools:::Rd_expr_doi("10.1002/bimj.201100214").

Examples

link <- 'cloglog'
attr(link, which="p") <- make.link(link)
parameter <- c(-0.68294630,0.03451481)
names(parameter) <- c('p','scale-factor')
model.name <- 'EPPM extended binomial'
ntrials <- list(c(rep(10,11)))
Model.JMVGB(parameter, model.name, link, ntrials, 
            covariates.matrix.p = matrix(c(1),nrow=1), 
            covariates.matrix.scalef = matrix(c(1),nrow=1), 
            offset.p = c(0), offset.scalef = c(0))