2 citations · 2 across the 7 of their papers we have counts for
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Bayesian Plackett--Luce latent block models for ranked data
Lapo Santi, Nial Friel, Valeria Vitelli
We introduce a Bayesian latent block model that jointly partitions assessors and items under a Plackett--Luce observation model. Assessors are assigned to clusters and items to…
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…
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…
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…