Change point analysis is an important topic when investigating renewal processes. One approach to detect multiple change points is the Multiple filter test (MFT) and was proposed by Messer et al. (2014), where change points are detected based on MOSUM (moving sum) statistics while using multiple symmetric bandwidths to detect different types of change points. Our goal in this project is to expand this approach to different situations, e.g. for asymmetric bandwidths or for the bandwidths being of different order than in the MFT. We will work on proving consistency results for both the estimators and the test statistics and try to make assertions about the order of the difference between the change point estimators and the change points. We intend to fit our methods to real-life data, e.g. neuronal spike trains.