Model.Faddy: Function for Faddy distribution with log link.

In CountsEPPM: Mean and Variance Modeling of Count Data

Description

Returns probabilities for a Faddy distribution given inputs of model and parameters.

Usage

Model.Faddy(parameter, model.name, link, covariates.matrix.mean,
 offset.mean, fixed.b, vnmax)

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 five 'Poisson', 'negative binomial', 'negative binomial fixed b', 'Faddy distribution', 'Faddy distribution fixed b'.
link	Takes one of one values i.e., 'log'. The default is 'log'.
covariates.matrix.mean	A matrix of covariates for the mean where rows are the number of values in listcounts and columns the covariates. This matrix is extracted from the formulae in function CountsEPPM. However, in the accompanying example it is shown how it can be constructed independently of function CountsEPPM.
offset.mean	An offset vector for the mean. The default is a vector of ones. This matrix is extracted from the formulae in function CountsEPPM.
fixed.b	Set to the value of the parameter b if a fixed.b model is being used.
vnmax	A vector of the maximum counts for each vector in list.counts i.e. the list of grouped counts.

Value

The list output with elements

model	The model being fitted
estimate	Estimates of parameters
probabilities	Vector of probabilities

Author(s)

David M. Smith <[e-mail]>

References

Faddy M, Smith D. (2011). Analysis of count data with covariate dependence in both mean and variance. Journal of Applied Statistics, 38, 2683-2694. doi: 10.1002/bimj.201100214.

Examples

all.counts=c(rep(0,5), 352, 479, 530, 291, 101, 17)
nmax1  <- length(all.counts)
nmax   <- nmax1 - 1
cnum   <- 0:nmax
ncount <- sum(all.counts)  
all.mean <- t(cnum) 
alldata <- data.frame(all.mean)
mf <- model.frame(formula = all.mean ~ 1, data = alldata)
covariates.matrix.mean <- model.matrix(attr(mf, "terms"), data = mf)
list.counts <- list(all.counts)
parameter <- c(53.047752, -13.205655, 3.801599)
names(parameter) <- c('log(a)', 'c', 'log(b)') 
model.name <- 'Faddy distribution'
link <- "log"
attr(link, which="mean") <- make.link(link)
offset.mean <- matrix(c(rep(0, nrow(covariates.matrix.mean))), ncol=1)
output <- Model.Faddy(parameter, model.name, link,
 covariates.matrix.mean, offset.mean, fixed.b = NA,
 vnmax = c(10))
print(output)

CountsEPPM documentation built on May 1, 2019, 10:25 p.m.