Abstract:
Point processes are a branch of spatial statistics mainly distinguish among the others by its commonly called “double stochasticity”, which refers to the fact that both: the location and the number of events happening are random. Classically, point processes have been studied in the Euclidean plane or at most three-dimensional space.
In the last decade, the increasing detail in spatial data collection, the much more information and accuracy on locations, have derived into the need of defining and analysing point processes on networks. In this talk we are going to present the main adjustments that need to be made to transfer the already existing tools from the Euclidean plane into networks, as well some applications where all these tools are undoubtably required.
