27 citations · 30 across the 3 of their papers we have counts for
4 papers
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…