37 citations · 85 across the 10 of their papers we have counts for
11 papers
Omitting continuous covariates in binary regression models: implications for sensitivity and mediation analysis
Matteo Gasparin, Bruno Scarpa, Elena Stanghellini
By exploiting the theory of skew-symmetric distributions, we generalise existing results in sensitivity analysis by providing the analytic expression of the bias induced by margina…
RanBox: Anomaly Detection in the Copula Space
Tommaso Dorigo, Martina Fumanelli, Chiara Maccani +3
The unsupervised search for overdense regions in high-dimensional feature spaces, where locally high population densities may be associated with anomalous contaminations to an othe…
Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider
Anna Stakia, Tommaso Dorigo, Giovanni Banelli +22
Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named "AMVA4NewPhysics" studied the customization and application of advanced multiv…
Dynamic modeling of mortality via mixtures of skewed distribution functions
Emanuele Aliverti, Stefano Mazzuco, Bruno Scarpa
There has been growing interest on forecasting mortality. In this article, we propose a novel dynamic Bayesian approach for modeling and forecasting the age-at-death distribution,…
Enriched Pitman-Yor processes
Tommaso Rigon, Bruno Scarpa, Sonia Petrone
In Bayesian nonparametrics there exists a rich variety of discrete priors, including the Dirichlet process and its generalizations, which are nowadays well-established tools. Despi…
Analysis of association football playing styles: an innovative method to cluster networks
Jacopo Diquigiovanni, Bruno Scarpa
In this work we develop an innovative hierarchical clustering method to divide a sample of undirected weighted networks into groups. The methodology consists of two phases: the fir…
Bayesian inference on group differences in multivariate categorical data
Massimiliano Russo, Daniele Durante, Bruno Scarpa
Multivariate categorical data are common in many fields. We are motivated by election polls studies assessing evidence of changes in voters opinions with their candidates preferenc…
Bayesian modeling of networks in complex business intelligence problems
Daniele Durante, Sally Paganin, Bruno Scarpa +1
Complex network data problems are increasingly common in many fields of application. Our motivation is drawn from strategic marketing studies monitoring customer choices of specifi…
Bayesian nonparametric location-scale-shape mixtures
Antonio Canale, Bruno Scarpa
Discrete mixture models are one of the most successful approaches for density estimation. Under a Bayesian nonparametric framework, Dirichlet process location-scale mixture of Gaus…
Informative Bayesian inference for the skew-normal distribution
Antonio Canale, Bruno Scarpa
Motivated by the analysis of the distribution of university grades, which is usually asymmetric, we discuss two informative priors for the shape parameter of the skew-normal distri…
Locally adaptive factor processes for multivariate time series
Daniele Durante, Bruno Scarpa, David B. Dunson
In modeling multivariate time series, it is important to allow time-varying smoothness in the mean and covariance process. In particular, there may be certain time intervals exhibi…