We review recent research on statistical methods for analysing spatial patterns of points on a
network of lines, such as road accident locations along a road network. Due to geometrical …

An extensive update to a classic text Stochastic geometry and spatial statistics play a
fundamental role in many modern branches of physics, materials sciences, engineering …

Within the applications of spatial point processes, it is increasingly becoming common that
events are labelled by marks, prompting an exploration beyond the spatial distribution of …

This paper develops a statistically principled approach to kernel density estimation on a
network of lines, such as a road network. Existing heuristic techniques are reviewed, and …

We propose a computationally efficient and statistically principled method for kernel
smoothing of point pattern data on a linear network. The point locations, and the network …

Voronoi estimators are non-parametric and adaptive estimators of the intensity of a point
process. The intensity estimate at a given location is equal to the reciprocal of the size of the …

We present several characteristics for spatio-temporal point patterns when the spatial
locations are restricted to a linear network. A nonparametric kernel-based intensity estimator …

In the literature on spatial point processes, there is an emerging challenge in studying
marked point processes with points being labelled by functions. In this paper, we focus on …

The rapidly expanding Himalayan road network connects rural mountainous regions.
However, the fragility of the landscape and poor road construction practices lead to frequent …

As a workaround for the lack of transitive transformations on linear network structures, which
are required to consider different notions of distributional invariance, including stationarity …