  We consider the structural change in a class of discrete valued time series
that the conditional distribution follows a one-parameter exponential family.
We propose a change-point test based on the maximum likelihood estimator of the
parameter of the model. Under the null hypothesis (of no change), the test
statistics converges to a well known distribution, allowing for the calculation
of the critical values of the test. The test statistic diverges to infinity
under the alternative, that is, the test asymptotically has power one. Some
simulation results and real data applications are reported to show the
applicability of the test procedure.
