1 citations · 2 across the 6 of their papers we have counts for
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Conjugate priors and bias reduction for logistic regression models
Tommaso Rigon, Emanuele Aliverti
Logistic regression models for binomial responses are routinely used in statistical practice. However, the maximum likelihood estimate may not exist due to data separability. We ad…
Bayesian nonparametric modelling of sequential discoveries
Alessandro Zito, Tommaso Rigon, Otso Ovaskainen +1
We aim at modelling the appearance of distinct tags in a sequence of labelled objects. Common examples of this type of data include words in a corpus or distinct species in a sampl…
Bayesian Testing for Exogenous Partition Structures in Stochastic Block Models
Sirio Legramanti, Tommaso Rigon, Daniele Durante
Network data often exhibit block structures characterized by clusters of nodes with similar patterns of edge formation. When such relational data are complemented by additional inf…
A generalized Bayes framework for probabilistic clustering
Tommaso Rigon, Amy H. Herring, David B. Dunson
Loss-based clustering methods, such as k-means and its variants, are standard tools for finding groups in data. However, the lack of quantification of uncertainty in the estimated…
An enriched mixture model for functional clustering
Tommaso Rigon
There is an increasingly rich literature about Bayesian nonparametric models for clustering functional observations. However, most of the recent proposals rely on infinite-dimensio…