7 papers
Bayesian Plackett--Luce latent block models for ranked data
Lapo Santi, Nial Friel, Valeria Vitelli
The paper proposes a Bayesian latent block model that jointly clusters assessors and items for ranked data using a Plackett–Luce observation model, with inference via Gibbs samplin…
Bayesian Conway-Maxwell-Poisson model with spike-and slab priors for dispersed count data with application to football scores
Nick Zhang, Riccardo Rastelli, Nial Friel
Statistical modeling for goals scored in football is typically achieved using the Poisson distribution and its variants. Here we propose a Bayesian framework for modeling under- an…
Ordering Stochastic Block Models via prior transitivity
Lapo Santi, Nial Friel, Pierpaolo De Blasi
In directed networks, nodes may form groups with similar interaction patterns, while these groups may themselves follow an ordered structure. Existing methods typically treat these…
A Zero-Inflated Poisson Latent Position Cluster Model
Chaoyi Lu, Riccardo Rastelli, Nial Friel
The latent position network model (LPM) is a popular approach for the statistical analysis of network data. A central aspect of this model is that it assigns nodes to random positi…
Bayesian Strategies for Repulsive Spatial Point Processes
Chaoyi Lu, Nial Friel
There is increasing interest to develop Bayesian inferential algorithms for point process models with intractable likelihoods. A purpose of this paper is to illustrate the utility…
The Bradley-Terry Stochastic Block Model
Lapo Santi, Nial Friel
The Bradley-Terry model is widely used for the analysis of pairwise comparison data and, in essence, produces a ranking of the items under comparison. We embed the Bradley-Terry mo…