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 …

We study a multivariate version of trend filtering, called Kronecker trend filtering or KTF, for
the case in which the design points form a lattice in $ d $ dimensions. KTF is a natural …

Trend filtering is a modern approach to nonparametric regression that is more adaptive to
local smoothness than splines or similar basis procedures. Existing analyses of trend …

The availability of large spatial data geocoded at accurate locations has fueled a growing
interest in spatial modeling and analysis of point processes. The proposed research is …

The supplementary material (Schneble and Kauermann (2022)) contains the data and the R-
source code to reproduce the results of the data analyses and the simulation study. The …

The availability of large-scale spatial and temporal data has fueled increasing interest in
statistical modelling and analysis. With the recent development of data collection and data …

Nonparametric density estimation is a fundamental task in statistics. In many applications,
such as clustering, non-parametric testing, classi? cation, anomaly detection and topological …

Intensity estimation is challenging for modern large-scale multivariate or marked point
process data. When the total number of events is large, the mark space is non-trivial or the …