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Autori principali: Artis, Amélie, Choiruddin, Achmad, Coeurjolly, Jean-François, Letué, Frédérique
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2512.23772
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author Artis, Amélie
Choiruddin, Achmad
Coeurjolly, Jean-François
Letué, Frédérique
author_facet Artis, Amélie
Choiruddin, Achmad
Coeurjolly, Jean-François
Letué, Frédérique
contents In this paper, we model the locations of five major banks in mainland France, two lucrative and three cooperative institutions based on socio-economic considerations. Locations of banks are collected using web scrapping and constitute a bivariate spatial point process for which we estimate nonparametrically summary functions (intensity, Ripley and cross-Ripley's K functions). This shows that the pattern is highly inhomogenenous and exhibits a clustering effect especially at small scales, and thus a significant departure to the bivariate (inhomogeneous) Poisson point process is pointed out. We also collect socio-economic datasets (at the living area level) from INSEE and propose a parametric modelling of the intensity function using these covariates. We propose a group-penalized bivariate composite likelihood method to estimate the model parameters, and we establish its asymptotic properties. The application of the methodology to the banking dataset provides new insights into the specificity of the cooperative model within the sector, particularly in relation to the theories of institutional isomorphism.
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id arxiv_https___arxiv_org_abs_2512_23772
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Marked point processes intensity estimation using sparse group Lasso method applied to locations of lucrative and cooperative banks in mainland France
Artis, Amélie
Choiruddin, Achmad
Coeurjolly, Jean-François
Letué, Frédérique
Methodology
Statistics Theory
In this paper, we model the locations of five major banks in mainland France, two lucrative and three cooperative institutions based on socio-economic considerations. Locations of banks are collected using web scrapping and constitute a bivariate spatial point process for which we estimate nonparametrically summary functions (intensity, Ripley and cross-Ripley's K functions). This shows that the pattern is highly inhomogenenous and exhibits a clustering effect especially at small scales, and thus a significant departure to the bivariate (inhomogeneous) Poisson point process is pointed out. We also collect socio-economic datasets (at the living area level) from INSEE and propose a parametric modelling of the intensity function using these covariates. We propose a group-penalized bivariate composite likelihood method to estimate the model parameters, and we establish its asymptotic properties. The application of the methodology to the banking dataset provides new insights into the specificity of the cooperative model within the sector, particularly in relation to the theories of institutional isomorphism.
title Marked point processes intensity estimation using sparse group Lasso method applied to locations of lucrative and cooperative banks in mainland France
topic Methodology
Statistics Theory
url https://arxiv.org/abs/2512.23772