activity
20242026
collaborators

5 papers

stat.CO2026

A new framework for non-stationary spatio-temporal data fusion of multi-fidelity models

Pietro Colombo, Fabio Sigrist, Claire Miller +3

We propose a new scalable framework for spatio-temporal data fusion with multi-fidelity Gaussian processes (MFGPs) that enables fully likelihood-based inference for both stationary…

stat.AP2026

On the use of satellite information to estimate agricultural carbon footprint in a small area framework

Riccardo Pajno, Felicetta Carillo, Paolo Maranzano +2

The agricultural sector is undergoing rapid change due to climate pressures, demographic shifts, and uneven economic development, increasing the demand for reliable environmental i…

stat.AP2025

Spatiotemporal clustering of GHGs emissions in Europe: exploring the role of spatial component

Caterina Morelli, Paolo Maranzano, Philipp Otto

In this study, we propose a novel application of spatiotemporal clustering in the environmental sciences, with a particular focus on regionalised time series of greenhouse gases (G…

stat.AP2024

Multidimensional spatiotemporal clustering -- An application to environmental sustainability scores in Europe

Caterina Morelli, Simone Boccaletti, Paolo Maranzano +1

The assessment of corporate sustainability performance is extremely relevant in facilitating the transition to a green and low-carbon intensity economy. However, companies located…

stat.ME2024

A review of regularised estimation methods and cross-validation in spatiotemporal statistics

Philipp Otto, Alessandro Fassò, Paolo Maranzano

This review article focuses on regularised estimation procedures applicable to geostatistical and spatial econometric models. These methods are particularly relevant in the case of…