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20202026
most citedSpatial Bayesian Hierarchical Modelling with Integrated Nested Laplace Approximation

13 citations · 37 across the 12 of their papers we have counts for

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9 papers · 1 filter

stat.ME2026

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…

stat.ME2024

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…

stat.ME2024

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,…

stat.ME2024

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…

stat.ME2023

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…

stat.ME2023

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…

stat.ME2022★ 12 cited

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…

stat.ME2022

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…

stat.ME2022★ 11 cited

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…