activity
20172022
most citedStructural Learning of Simple Staged Trees

2 citations · 6 across the 7 of their papers we have counts for

collaborators

12 papers

stat.ML20222 cited

Structural Learning of Simple Staged Trees

Manuele Leonelli, Gherardo Varando

Bayesian networks faithfully represent the symmetric conditional independences existing between the components of a random vector. Staged trees are an extension of Bayesian network…

stat.ML2021

Global sensitivity analysis in probabilistic graphical models

Rafael Ballester-Ripoll, Manuele Leonelli

We show how to apply Sobol's method of global sensitivity analysis to measure the influence exerted by a set of nodes' evidence on a quantity of interest expressed by a Bayesian ne…

stat.ME20211 cited

Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package

Manuele Leonelli, Ramsiya Ramanathan, Rachel L. Wilkerson

Bayesian networks are a class of models that are widely used for risk assessment of complex operational systems. There are now multiple approaches, as well as implemented software,…

stat.ME20202 cited

Tracking change-points in multivariate extremes

Miguel de Carvalho, Manuele Leonelli, Alex Rossi

In this paper we devise a statistical method for tracking and modeling change-points on the dependence structure of multivariate extremes. The methods are motivated by and illustra…

stat.ME2020

The R Package stagedtrees for Structural Learning of Stratified Staged Trees

Federico Carli, Manuele Leonelli, Eva Riccomagno +1

stagedtrees is an R package which includes several algorithms for learning the structure of staged trees and chain event graphs from data. Score-based and clustering-based algorith…

q-fin.ST2019

A changepoint approach for the identification of financial extreme regimes

Chiara Lattanzi, Manuele Leonelli

Inference over tails is usually performed by fitting an appropriate limiting distribution over observations that exceed a fixed threshold. However, the choice of such threshold is…