Identification of neighborhood clusters on data balanced by a poset-based approach

DOI10.1007/s10260-023-00695-0OpenAlexW4368376902MaRDI QIDQ6088749

Margherita Silan, Pietro Belloni, Giovanna Boccuzzo

Publication date: 14 December 2023

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-023-00695-0

zbMATH Keywords

posetneighborhood effectbalancepublic healthgeographical clusters

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Bayesian scanning of spatial disease rates with integrated nested Laplace approximation (INLA)
• Spatial scan statistics in loglinear models
• Evaluating inverse propensity score weighting in the presence of many treatments. An application to the estimation of the neighbourhood effect
• A comparison of machine learning algorithms and covariate balance measures for propensity score matching and weighting
• Clustering of Random Points in Two Dimensions
• A Spatial Scan Statistic for Survival Data
• Unnamed Item
• Unnamed Item

This page was built for publication: Identification of neighborhood clusters on data balanced by a poset-based approach