37 citations · 114 across the 12 of their papers we have counts for
13 papers
Modeling Spatio-Temporal Dynamics of Obesity in Italian Regions Via Bayesian Beta Regression
Luciano Rota, Raffaele Argiento, Michela Cameletti
In this paper we investigate the spatio-temporal dynamics of obesity rates across Italian regions from 2010 to 2022, aiming to identify spatial and temporal trends and assess poten…
INLA-RF: A Hybrid Modeling Strategy for Spatio-Temporal Environmental Data
Mario Figueira, Michela Cameletti, Luca Patelli
Environmental processes often exhibit complex, non-linear patterns and discontinuities across space and time, posing significant challenges for traditional geostatistical modeling…
S-SIRUS: an explainability algorithm for spatial regression Random Forest
Luca Patelli, Natalia Golini, Rosaria Ignaccolo +1
Random Forest (RF) is a widely used machine learning algorithm known for its flexibility, user-friendliness, and high predictive performance across various domains. However, it is…
Spatiotemporal modelling of PM concentrations in Lombardy (Italy) -- A comparative study
Philipp Otto, Alessandro Fusta Moro, Jacopo Rodeschini +7
This study presents a comparative analysis of three predictive models with an increasing degree of flexibility: hidden dynamic geostatistical models (HDGM), generalised additive mi…
A path in regression Random Forest looking for spatial dependence: a taxonomy and a systematic review
Luca Patelli, Michela Cameletti, Natalia Golini +1
Random Forest (RF) is a well-known data-driven algorithm applied in several fields thanks to its flexibility in modeling the relationship between the response variable and the pred…
Bayesian Inference for Multivariate Spatial Models with R-INLA
Francisco Palmí-Perales, Virgilio Gómez-Rubio, Roger S Bivand +2
Bayesian methods and software for spatial data analysis are generally now well established in the scientific community. Despite the wide application of spatial models, the analysis…
Agrimonia: a dataset on livestock, meteorology and air quality in the Lombardy region, Italy
Alessandro Fassò, Jacopo Rodeschini, Alessandro Fusta Moro +7
The air in the Lombardy region, Italy, is one of the most polluted in Europe because of limited air circulation and high emission levels. There is a large scientific consensus that…
A framework for estimating and visualising excess mortality during the COVID-19 pandemic
Garyfallos Konstantinoudis, Virgilio Gómez-Rubio, Michela Cameletti +3
COVID-19 related deaths underestimate the pandemic burden on mortality because they suffer from completeness and accuracy issues. Excess mortality is a popular alternative, as it c…
A spatio-temporal analysis of NO concentrations during the Italian 2020 COVID-19 lockdown
Guido Fioravanti, Michela Cameletti, Sara Martino +2
When a new environmental policy or a specific intervention is taken in order to improve air quality, it is paramount to assess and quantify - in space and time - the effectiveness…
Spatio-temporal modelling of daily concentrations in Italy using the SPDE approach
Guido Fioravanti, Sara Martino, Michela Cameletti +1
This paper illustrates the main results of a spatio-temporal interpolation process of concentrations at daily resolution using a set of 410 monitoring sites, distr…
A joint bayesian space-time model to integrate spatially misaligned air pollution data in R-INLA
Chiara Forlani, Samir Bhatt, Michela Cameletti +2
In air pollution studies, dispersion models provide estimates of concentration at grid level covering the entire spatial domain, and are then calibrated against measurements from m…
Missing data analysis and imputation via latent Gaussian Markov random fields
Virgilio Gómez-Rubio, Michela Cameletti, Marta Blangiardo
In this paper we recast the problem of missing values in the covariates of a regression model as a latent Gaussian Markov random field (GMRF) model in a fully Bayesian framework. O…
Comparing air quality statistical models
Michela Cameletti, Rosaria Ignaccolo, Stefano Bande
Air pollution is a great concern because of its impact on human health and on the environment. Statistical models play an important role in improving knowledge of this complex spat…