3 citations · 7 across the 10 of their papers we have counts for
11 papers
Bayesian spatio-temporal exposure modelling of air pollution in Rome, Italy, and short-term effects on cause-specific mortality
Edoardo Rosci, Giovanna Jona Lasinio, Paola Michelozzi +1
Assessing fine-scale spatio-temporal air pollution contrasts in urban contexts is a major challenge for environmental epidemiology. We propose a Bayesian spatio-temporal model to p…
Scalable model selection for count time series with structural breaks: application to solid-organ transplantation during and after COVID-19 in the USA and Italy
Tobia Filosi, Emiliano Ceccarelli, Emilio Porcu +7
Weekly healthcare activity data are typically non-negative counts with temporal dependence and occasional system-wide disruptions, settings in which Gaussian time-series models may…
A two-stage approach to heat-mortality risk assessment comparing multiple exposure-to-temperature models: the case study in Lazio, Italy
Emiliano Ceccarelli, Jorge Castillo-Mateo, Sandra Gudžiūnaitė +3
This study investigates how different spatiotemporal temperature models affect the estimation of heat-related mortality in Lazio, Italy (2008--2022). First, we compare three method…
Modelling benthic animals in space and time using Bayesian Point Process with cross validation: the case of Holoturians
Daniele Poggio, Gian Mario Sangiovanni, Gianluca Mastrantonio +4
Understanding the spatial distribution of Holothurians is an essential task for ecosystem monitoring and sustainable management, particularly in the Mediterranean habitats. However…
Bayesian size-and-shape regression modelling
Antonio Di Noia, Gianluca Mastrantonio, Giovanna Jona Lasinio
Building on Dryden et al. (2021), this note presents the Bayesian estimation of a regression model for size-and-shape response variables with Gaussian landmarks. Our proposal fits…
Spatial modelling of COVID-19 incident cases using Richards' curve: an application to the Italian regions
Marco Mingione, Pierfrancesco Alaimo Di Loro, Alessio Farcomeni +4
We introduce an extended generalised logistic growth model for discrete outcomes, in which a network structure can be specified to deal with spatial dependence and time dependence…
A Hierarchical Multivariate Spatio-Temporal Model for Large Clustered Climate data with Annual Cycles
Gianluca Mastrantonio, Giovanna Jona Lasinio, Alessio Pollice +4
We present a multivariate hierarchical space-time model to describe the joint series of monthly extreme temperatures and amounts of rainfall. Data are available for 360 monitoring…
Assessing the role of the spatial scale in the analysis of lagoon biodiversity. A case-study on the macrobenthic fauna of the Po River Delta
Giovanna Jona Lasinio, Alessio Pollice, Eric Marcon +1
The analysis of benthic assemblages is a valuable tool to describe the ecological status of transitional water ecosystems, but species are extremely sensitive and respond to both m…
On initial direction, orientation and discreteness in the analysis of circular variables
Gianluca Mastrantonio, Giovanna Jona Lasinio, Antonello Maruotti +1
In this paper, we propose a discrete circular distribution obtained by extending the wrapped Poisson distribution. This new distribution, the Invariant Wrapped Poisson (IWP), enjoy…
Tools for predicting rainfall from lightning records: events identification and rain prediction using a Bayesian hierarchical model
Edmondo Di Giuseppe, Giovanna Jona Lasinio, Massimiliano Pasqui +1
We propose a new statistical protocol for the estimation of precipitation using lightning data. We first identify rainy events using a scan statistics, then we estimate Rainfall Li…
Bayesian Modeling and MCMC Computation in Linear Logistic Regression for Presence-only Data
Fabio Divino, Natalia Golini, Giovanna Jona Lasinio +1
Presence-only data are referred to situations in which, given a censoring mechanism, a binary response can be observed only with respect to on outcome, usually called \textit{prese…