activity
20172021
most citedpivmet: Pivotal Methods for Bayesian Relabelling and k-Means Clustering

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

stat.CO20211 cited

pivmet: Pivotal Methods for Bayesian Relabelling and k-Means Clustering

Leonardo Egidi, Roberta Pappadà, Francesco Pauli +1

The identification of groups' prototypes, i.e. elements of a dataset that represent different groups of data points, may be relevant to the tasks of clustering, classification and…

stat.AP2020

Mendelian Randomization with Incomplete Exposure Data: a Bayesian Approach

Teresa Fazia, Leonardo Egidi, Burcu Ayoglu +9

We expand Mendelian Randomization (MR) methodology to deal with randomly missing data on either the exposure or the outcome variable, and furthermore with data from nonindependent…

stat.AP2019

A Bayesian Quest for Finding a Unified Model for Predicting Volleyball Games

Leonardo Egidi, Ioannis Ntzoufras

Volleyball is a team sport with unique and specific characteristics. We introduce a new two level-hierarchical Bayesian model which accounts for theses volleyball specific characte…

stat.AP2019

Bayesian Mendelian Randomization identifies disease causing proteins via pedigree data, partially observed exposures and correlated instruments

Teresa Fazia, Leonardo Egidi, Burcu Ayoglu +7

Background In a study performed on multiplex Multiple Sclerosis (MS) Sardinian families to identify disease causing plasma proteins, application of Mendelian Randomization (MR) met…

stat.AP2018

Combining historical data and bookmakers'odds in modelling football scores

Leonardo Egidi, Francesco Pauli, Nicola Torelli

Modelling football outcomes has gained increasing attention, in large part due to the potential for making substantial profits. Despite the strong connection existing between footb…

stat.ME2017

Mixture Data-Dependent Priors

Leonardo Egidi, Francesco Pauli, Nicola Torelli

We propose a two-component mixture of a noninformative (diffuse) and an informative prior distribution, weighted through the data in such a way to prefer the first component if a p…