6 citations · 10 across the 12 of their papers we have counts for
15 papers
Stochastic Bayes factors: why, when, and how
Leonardo Egidi, Ioannis Ntzoufras
The Bayes factor (BF) is a central tool in Bayesian hypothesis testing and model selection, yet its practical use is often challenged. Classical BFs depend heavily on prior specifi…
Leicester's Tale: Another Perspective on the EPL 2015/16 Through Expected Goals (xG) Modelling
Sheikh Badar Ud Din Tahir, Leonardo Egidi, Nicola Torelli
Probabilistic modeling is an effective tool for evaluating team performance and predicting outcomes in sports. However, an important question that hasn't been fully explored is whe…
Bayesian weighted discrete-time dynamic models for association football prediction
Roberto Macrì-Demartino, Leonardo Egidi, Nicola Torelli
In recent years, great emphasis has been placed on the prediction of association football. Due to this, several studies have proposed different types of statistical models to predi…
Eliciting prior information from clinical trials via calibrated Bayes factor
Roberto Macrì Demartino, Leonardo Egidi, Nicola Torelli +1
In the Bayesian framework power prior distributions are increasingly adopted in clinical trials and similar studies to incorporate external and past information, typically to infor…
Mixture priors for replication studies
Roberto Macrì-Demartino, Leonardo Egidi, Leonhard Held +1
Replication of scientific studies is important for assessing the credibility of their results. However, there is no consensus on how to quantify the extent to which a replication s…
Alternative ranking measures to predict international football results
Roberto Macrì Demartino, Leonardo Egidi, Nicola Torelli
Over the last few years, there has been a growing interest in the prediction and modelling of competitive sports outcomes, with particular emphasis placed on this area by the Bayes…
Assessing replication success via skeptical mixture priors
Guido Consonni, Leonardo Egidi
There is a growing interest in the analysis of replication studies of original findings across many disciplines. When testing a hypothesis for an effect size, two Bayesian approach…
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…
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…
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…
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…
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…
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…
Maxima Units Search (MUS) algorithm: methodology and applications
Leonardo Egidi, Roberta Pappadà, Francesco Pauli +1
An algorithm for extracting identity submatrices of small rank and pivotal units from large and sparse matrices is proposed. The procedure has already been satisfactorily applied f…
Relabelling in Bayesian mixture models by pivotal units
Leonardo Egidi, Roberta Pappadà, Francesco Pauli +1
In this paper a simple procedure to deal with label switching when exploring complex posterior distributions by MCMC algorithms is proposed. Although it cannot be generalized to an…