115 citations · 116 across the 8 of their papers we have counts for
12 papers
Bayesian perspectives on exponential random graph models
Alberto Caimo, Isabella Gollini
Exponential random graph models (ERGMs) are a widely used framework for network data, enabling hypothesis testing on the structural mechanisms underlying observed networks. Bayesia…
Multi-layer dissolution exponential-family models for weighted signed networks
Alberto Caimo, Isabella Gollini
Understanding the structure of weighted signed networks is essential for analysing social systems in which relationships vary both in sign and strength. Despite significant advance…
Separable models for dynamic signed networks
Alberto Caimo, Isabella Gollini
Signed networks capture the polarity of relationships between nodes, providing valuable insights into complex systems where both supportive and antagonistic interactions play a cri…
LAMSkyCam: A Low-cost and Miniature Ground-based Sky Camera
Mayank Jain, Vishal Singh Sengar, Isabella Gollini +3
Ground-based sky imagers (GSIs) are increasingly becoming popular amongst the remote sensing analysts. This is because such imagers offer fantastic alternatives to satellite measur…
An Extremely-low Cost Ground-Based Whole Sky Imager
Mayank Jain, Isabella Gollini, Michela Bertolotto +2
Ground-based Whole Sky Imagers (WSIs) are increasingly being used for various remote sensing applications. While the fundamental requirements of a WSI are to make it climate-proof…
A mixture model approach for clustering bipartite networks
Isabella Gollini
This chapter investigates the latent structure of bipartite networks via a model-based clustering approach which is able to capture both latent groups of sending nodes and latent v…
A multilayer exponential random graph modelling approach for weighted networks
Alberto Caimo, Isabella Gollini
A new modelling approach for the analysis of weighted networks with ordinal/polytomous dyadic values is introduced. Specifically, it is proposed to model the weighted network conne…
Rapidly bounding the exceedance probabilities of high aggregate losses
Isabella Gollini, Jonathan Rougier
We consider the task of assessing the righthand tail of an insurer's loss distribution for some specified period, such as a year. We present and analyse six different approaches: f…
Bayesian computational algorithms for social network analysis
Alberto Caimo, Isabella Gollini
In this chapter we review some of the most recent computational advances in the rapidly expanding field of statistical social network analysis using the R open-source software. In…
GWmodel: an R Package for Exploring Spatial Heterogeneity using Geographically Weighted Models
Isabella Gollini, Binbin Lu, Martin Charlton +2
Spatial statistics is a growing discipline providing important analytical techniques in a wide range of disciplines in the natural and social sciences. In the R package GWmodel, we…
Mixture of Latent Trait Analyzers for Model-Based Clustering of Categorical Data
Isabella Gollini, Thomas Brendan Murphy
Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical d…
Joint Modelling of Multiple Network Views
Isabella Gollini, Thomas Brendan Murphy
Latent space models (LSM) for network data were introduced by Hoff et al. (2002) under the basic assumption that each node of the network has an unknown position in a D-dimensional…