13 citations · 40 across the 17 of their papers we have counts for
12 papers · 1 filter
Testing the Structural Properties of Marked Point Processes Using Local Inhomogeneous Mark-Weighted K-Functions
Nicoletta D'Angelo, Giada Adelfio, Matthias Eckardt
This work proposes -type test statistics to assess different hypotheses on the local structure of an observed marked point pattern. The test statistics is based on the local i…
Detecting changes in space-varying parameters of local Poisson point processes
Nicoletta D'Angelo
Recent advances in local models for point processes have highlighted the need for flexible methodologies to account for the spatial heterogeneity of external covariates influencing…
stopp: An R Package for Spatio-Temporal Point Pattern Analysis
Nicoletta D'Angelo, Giada Adelfio
stopp is a novel R package specifically designed for the analysis of spatio-temporal point patterns which might have occurred in a subset of the Euclidean space or on some specific…
Testing for a general changepoint in psychometric studies: changes detection and sample size planning
Nicoletta D'Angelo
This paper introduces a new method for change detection in psychometric studies based on the recently introduced pseudo Score statistic, for which the sampling distribution under t…
Semi-parametric profile pseudolikelihood via local summary statistics for spatial point pattern intensity estimation
Nicoletta D'Angelo, Giada Adelfio, Jorge Mateu +1
Second-order statistics play a crucial role in analysing point processes. Previous research has specifically explored locally weighted second-order statistics for point processes,…
Cubature scheme for spatio-temporal Poisson point processes estimation
Nicoletta D'Angelo, Giada Adelfio
This work presents the cubature scheme for the fitting of spatio-temporal Poisson point processes. The methodology is implemented in the R Core Team (2024) package stopp (D'Angelo…
Advances in Kth nearest-neighbour clutter removal
Nicoletta D'Angelo
We consider the problem of feature detection in the presence of clutter in spatial point processes. Classification methods have been developed in previous studies. Among these, Bye…
Minimum contrast for the first-order intensity estimation of spatial and spatio-temporal point processes
Nicoletta D'Angelo, Giada Adelfio
In this paper, we harness a result in point process theory, specifically the expectation of the weighted -function, where the weighting is done by the true first-order intensity…
stopp: Methods for spatio-temporal point pattern analysis, simulation, model fitting, diagnostics, and local analyses
Nicoletta D'Angelo, Giada Adelfio
The stopp R package deals with spatio-temporal point processes which might have occurred on the Euclidean space or on some specific linear networks such as roads of a city. The pac…
Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes
Nicoletta D'Angelo, Giada Adelfio, Jorge Mateu
We propose a local version of spatio-temporal log-Gaussian Cox processes using Local Indicators of Spatio-Temporal Association (LISTA) functions into the minimum contrast procedure…
Feature detection in point processes on linear networks using nearest neighbour volumes
Juan F. Diaz-Sepulveda, Nicoletta D'Angelo, Giada Adelfio +2
We consider the feature detection problem in the presence of clutter in point processes on linear networks. We extend the classification method developed in previous studies to thi…
Local inhomogeneous weighted summary statistics for marked point processes
Nicoletta D'Angelo, Giada Adelfio, Jorge Mateu +1
We introduce a family of local inhomogeneous mark-weighted summary statistics, of order two and higher, for general marked point processes. Depending on how the involved weight fun…