  The analysis of spatial point patterns that occur in the network domain have
recently gained much attraction and various intensity functions and measures
have been proposed. However, the linkage of spatial network statistics to
regression models has not been approached so far. This paper presents a new
regression approach which treats a generic intensity function of a planar point
pattern that occurred on a network as the outcome of a set of different
covariates and various graph statistics. Different to all alternative
approaches, our model is the first which permits the statistical analysis of
complex regression data in the context of network intensity functions for
spatial point patterns. The potential of our new technique to model the
structural dependencies of network intensity functions on various covariates
and graph statistics is illustrated using call-in data on neighbour and
community disturbances in an urban context.
