The estimation of the regression coefficients in the Poisson
regression model is not obtained with a direct equation, but the
Newton-Raphson iteration procedure is used for estimating the unknown
parameters of the model. To perform the estimation process,
the corresponding iteration algorithm is analyzed by SAS statistical
software to obtain the calculated coefficients. The predicted value of ŷi
is the conditional mean or average number of accidents given xi,
which is also denoted as λi, that is, the mean of the random variable yi,
which follows a Poisson distribution. This value is typically not an
integer number, whereas the observed value yi is a count (Anselin,
To estimate β and r*, as in the Poisson model, the iteration procedure
of Newton-Raphson is applied (Agresti, 2002). The related
iteration algorithm is written in SAS to obtain the unknown parameters.
In the NB regression model, the predicted value of ŷi is the
conditional mean or average number of accidents given xi. This is also
denoted as μi, that is, the mean of the random variable yi, which
follows the NB distribution.