1 citations · 1 across the 10 of their papers we have counts for
11 papers
Bayesian nonparametric clustering for spatio-temporal data, with an application to air pollution
Luca Aiello, Raffaele Argiento, Sirio Legramanti +1
Air pollution is a major global health hazard, with fine particulate matter (PM10) linked to severe respiratory and cardiovascular diseases. Hence, analyzing and clustering spatio-…
Bootstrap-based tests for the total time on test and the excess wealth orders
Tommaso Lando, Sirio Legramanti
Given a pair of non-negative random variables and , we introduce a class of nonparametric tests for the null hypothesis that dominates in the total time on test orde…
A new class of nonparametric tests for second-order stochastic dominance based on the Lorenz P-P plot
Tommaso Lando, Sirio Legramanti
Given samples from two non-negative random variables, we propose a family of tests for the null hypothesis that one random variable stochastically dominates the other at the second…
Learning and forecasting of age-specific period mortality via B-spline processes with locally-adaptive dynamic coefficients
Federico Pavone, Sirio Legramanti, Daniele Durante
Although the analysis of human mortality has a well-established history, the attempt to accurately forecast future death-rate patterns for different age groups and time horizons st…
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity
Sirio Legramanti, Daniele Durante, Pierre Alquier
There has been increasing interest on summary-free solutions for approximate Bayesian computation (ABC) which replace distances among summaries with discrepancies between the empir…
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…
Variational Bayes for Gaussian Factor Models under the Cumulative Shrinkage Process
Sirio Legramanti
The cumulative shrinkage process is an increasing shrinkage prior that can be employed within models in which additional terms are supposed to play a progressively negligible role.…
Extended Stochastic Block Models with Application to Criminal Networks
Sirio Legramanti, Tommaso Rigon, Daniele Durante +1
Reliably learning group structures among nodes in network data is challenging in several applications. We are particularly motivated by studying covert networks that encode relatio…
Bayesian cumulative shrinkage for infinite factorizations
Sirio Legramanti, Daniele Durante, David B. Dunson
There is a wide variety of models in which the dimension of the parameter space is unknown. For example, in factor analysis the number of latent factors is typically not known and…
Mean and dispersion of harmonic measure
Sirio Legramanti
In this note, we provide and prove exact formulas for the mean and the trace of the covariance matrix of harmonic measure, regarded as a parametric probability distribution.
Bayesian Analysis of Privacy Attacks on GPS Trajectories
Sirio Legramanti
The success of applications for sharing GPS trajectories raises serious privacy concerns, in particular about users' home addresses. In this paper we show that a Bayesian approach…