7 papers
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…
Using a neural network approach and starspots dependent models to predict effective temperatures and ages of young stars
Marco Tarantino, Loredana Prisinzano, Nicoletta D Angelo +2
This study presents a statistical approach to accurately predict the effective temperatures of pre-main sequence stars, which are necessary for determining stellar ages using the 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…
A point process approach for the classification of noisy calcium imaging data
Arianna Burzacchi, Nicoletta D'Angelo, David Payares-Garcia +1
We study noisy calcium imaging data, with a focus on the classification of spike traces. As raw traces obscure the true temporal structure of neuron's activity, we performed a tune…
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…