A log link is used for regression of the model parameters
\(\lambda\) and \(\nu\), that is: $$\log(\lambda) = \beta
X$$ $$\log(\nu) = \zeta Y$$
where: \(\beta\) is the vector of coefficients for the parameter
\(\lambda\), \(\zeta\) is the vector of coefficients for the
parameter \(\nu\), \(X\) is the model matrix for the parameter
\(\lambda\), and \(Y\) is the model matrix for the parameter
\(\nu\).
The parameter vectors are calculated via maximum likelihood using the
general optimisation function optim
. A Poisson model will
be fit using glm.fit
and (unless starting values are
supplied) the coefficients will be used as starting values for the
parameter vector \(\beta\).
Several S3 functions have been implemented for model analysis
print
, coef
, extractAIC
,
logLik
, predict
, and summary
,