On the trend detection of time-ordered intensity images of point processes on linear networks

Spatial point processes on linear networks are increasingly getting attention in different disciplines such as traffic accidents and street crime analysis. Dealing with a set of time-ordered patterns network over period, helps obtaining time series estimated intensity images. In this article, we combine the problem estimating relative risk trend detection observations. Taking temporal autocorrelation between consecutive images into account, make use Mann–Kendall test to look for potential locations where and/or show evidence monotonic trend. The monthly spatial fatal crimes city London, UK, period January 2013 December 2017, used an application.