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stat.ME2025
Generalized network autoregressive modelling of longitudinal networks with application to presidential elections in the USA
Guy Nason, Daniel Salnikov, Mario Cortina-Borja
Longitudinal networks are becoming increasingly relevant in the study of dynamic processes characterised by known or inferred community structure. Generalised Network Autoregressiv…
stat.ME2024
Modelling clusters in network time series with an application to presidential elections in the USA
Guy Nason, Daniel Salnikov, Mario Cortina-Borja
Network time series are becoming increasingly relevant in the study of dynamic processes characterised by a known or inferred underlying network structure. Generalised Network Auto…
stat.ME2023
New tools for network time series with an application to COVID-19 hospitalisations
Guy Nason, Daniel Salnikov, Mario Cortina-Borja
Network time series are becoming increasingly important across many areas in science and medicine and are often characterised by a known or inferred underlying network structure, w…