Abstract
This contribution deals with tests on the stability of statistical models. The problem is formulated in terms of testing the null hypothesis against the alternative hypothesis.
The null hypothesis claims that the model remains the same during the whole observational period, usually it means that the parameters of the model do not change. The alternative hypothesis claims that, at an unknown time point, the model changes, which means that some of the parameters of the model are subject to a~change.
We consider both Bayesian type procedures as well as procedures based on the maximum likelihood principle.