  The statistical analysis of structured spatial point process data where the
event locations are determined by an underlying spatially embedded relational
system has become a vivid field of research. Despite a growing literature on
different extensions of point process characteristics to linear network
domains, most software implementations remain restricted to either directed or
undirected network structures and are of limited use for the analysis of rather
complex real-world systems consisting of both undirected and directed parts.
Formalizing the network through a graph theoretic perspective, this paper
discusses a complementary approach for the analysis of network-based event data
through generic network intensity functions and gives a general introduction to
the intensitynet package implemented in R covering both computational details
and applications. By treating the edges as fundamental entities, the
implemented approach allows the computation of intensities and other related
values related to different graph structures containing undirected, directed,
or a combination of both edges as special cases. The package includes
characteristics for network modeling, data manipulation, intensity estimation,
computation of local and global autocorrelation statistics, visualization, and
extensions to marked point process scenarios. All functionalities are
accompanied by reproducible code examples using the chicago data as toy example
to illustrate the application of the package.
