Juan F. Diaz-Sepulveda
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Juan F. Diaz-Sepulveda has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
Francisco J. Rodriguez-Cortes
Escuela de Estadística Universidad Nacional de Colombia Medellín Colombia
1 shared publicationGiada Adelfio
Dipartimento di Scienze Economiche Aziendali e Statistiche Università degli Studi di Palermo Palermo Italy
1 shared publication- Jonatan Gonzalez-Monsalvo
Centre of Operations Research, Miguel Hernández University of Elche, 03202 Elche, Spain
1 shared publication Nicoletta D'Angelo
Dipartimento di Scienze Economiche Aziendali e Statistiche Università degli Studi di Palermo Palermo Italy
1 shared publication
Latest Publications
- Open Access
Feature detection in point processes on linear networks using nearest neighbour volumes
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 this more complex geometric context, where the classical properties of a point process change and data visualization are not intuitive. We use the K-th nearest neighbour volumes distribution in linear networks for this approach. As a result, our method is suitable for analysing point patterns consisting of features and clutter as two superimposed Poisson processes on the same linear network. To illustrate the method, we present simulations and examples of road traffic accidents that resulted in injuries or deaths in two cities in Colombia.
Open AccessFeature detection in point processes on linear networks using nearest neighbour volumes
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 this more complex geometric context, where the classical properties of a point process change and data visualization are not intuitive. We use the K-th nearest neighbour volumes distribution in linear networks for this approach. As a result, our method is suitable for analysing point patterns consisting of features and clutter as two superimposed Poisson processes on the same linear network. To illustrate the method, we present simulations and examples of road traffic accidents that resulted in injuries or deaths in two cities in Colombia.