26 citations · 52 across the 7 of their papers we have counts for
8 papers
Integrating Deep Learning and Spatial Statistics in Marine Ecosystem Monitoring
Gian Mario Sangiovanni, Gianluca Mastrantonio, Daniele Ventura +2
In ecology, photogrammetry is a crucial method for efficiently collecting non-destructive samples of natural environments. When estimating the spatial distribution of animals, dete…
Finite mixtures in capture-recapture surveys for modelling residency patterns in marine wildlife populations
Gianmarco Caruso, Pierfrancesco Alaimo Di Loro, Marco Mingione +3
In this work, the goal is to estimate the abundance of an animal population using data coming from capture-recapture surveys. We leverage the prior knowledge about the population's…
Nowcasting COVID-19 incidence indicators during the Italian first outbreak
Pierfrancesco Alaimo Di Loro, Fabio Divino, Alessio Farcomeni +4
A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal is motivated by real-time monitoring and short-term forecas…
Modeling "Equitable and Sustainable Well-being" (BES) using Bayesian Networks: A Case Study of the Italian regions
Federica Onori, Giovanna Jona Lasinio
Measurement of well-being has been a highly debated topic since the end of the last century. While some specific aspects are still open issues, a multidimensional approach as well…
CircSpaceTime: an R package for spatial and spatio-temporal modeling of Circular data
Giovanna Jona Lasinio, Mario Santoro, Gianluca Mastrantonio
CircSpaceTime is the only R package currently available that implements Bayesian models for spatial and spatio-temporal interpolation of circular data. Such data are often found in…
Bayesian Measurement Error Correction in Structured Additive Distributional Regression with an Application to the Analysis of Sensor Data on Soil-Plant Variability
Alessio Pollice, Giovanna Jona Lasinio, Roberta Rossi +3
The flexibility of the Bayesian approach to account for covariates with measurement error is combined with semiparametric regression models for a class of continuous, discrete and…
The wrapped skew Gaussian process for analyzing spatio-temporal data
Gianluca Mastrantonio, Giovanna Jona Lasinio, Alan E. Gelfand
We consider modeling of angular or directional data viewed as a linear variable wrapped onto a unit circle. In particular, we focus on the spatio-temporal context, motivated by a c…
Spatio-temporal circular models with non-separable covariance structure
Gianluca Mastrantonio, Giovanna Jona Lasinio, Alan E. Gelfand
Circular data arise in many areas of application. Recently, there has been interest in looking at circular data collected separately over time and over space. Here, we extend some…