Methods for marked spatial point processes with scalar marks have seen extensive
development in recent years. While the impressive progress in data collection and storage …

Testing for a covariate effect in a parametric point process model is usually done through the
Wald test, which relies on an asymptotic null distribution of the test statistic. We propose a …

This paper introduces several depths for random sets with possibly non-convex realisations,
proposes ways to estimate the depths based on the samples and compares them with …

First-order separability of a spatio-temporal point process plays a fundamental role in the
analysis of spatio-temporal point pattern data. While it is often a convenient assumption that …

In this paper, we propose a new robust non-parametric functional analysis of variance
method (RoFANOVA) that reduces the weights of outlying curves on the functional analysis …

Classical tests are available for the two-sample test of correspondence of distribution
functions. From these, the Kolmogorov–Smirnov test provides also the graphical …

Monte Carlo tests are widely used for computing valid p-values without requiring known
distributions of test statistics. When performing multiple Monte Carlo tests, it is essential to …

Classical tests are available for the two-sample test of correspondence of distribution
functions. From these, the Kolmogorov-Smirnov test provides also the graphical …

Quantile regression is used to study effects of covariates on a particular quantile of the data
distribution. Here we are interested in the question whether a covariate has any effect on the …

Several new methods have been recently developed for the problem of domain selection
when the test statistic is functional. That is, the aim is to distinguish between the two domains …