A1044
Title: A change point test for a gradual change in the Poisson INARCH(1)-process
Authors: Florian Schirra - Fraunhofer ITWM (Germany) [presenting]
Stefanie Schwaar - Fraunhofer ITWM (Germany)
Joern Sass - RPTU Kaiserslautern-Landau (Germany)
Abstract: Change point detection methods are a common tool to identify structural changes in the distribution of time series. In recent years, there has been progress in detecting changes within times series in countable spaces, e.g. the natural numbers. For a number of applications, such as outbreak detection of infectious diseases, modeling a gradual change could be valuable. Such count time series can be modeled by Poisson INARCH(1) processes. One possibility to model gradual changes is by introducing a non-linear time-dependent factor in the intensity function of a Poisson INARCH(1) process. This additional factor characterizes the gradual change after the change point. The distribution of a test statistic based on partial sums of weighted residuals still has a limiting distribution given by the Gumbel extreme value distribution under the null hypothesis. Under the alternative, consistency holds for certain assumptions.
