37 citations · 61 across the 7 of their papers we have counts for
8 papers
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…
Functional zoning of biodiversity profiles
Natalia Golini, Rosaria Ignaccolo, Luigi Ippoliti +1
Spatial mapping of biodiversity is crucial to investigate spatial variations in natural communities. Several indices have been proposed in the literature to represent biodiversity…
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…
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…
Bootstrap based uncertainty bands for prediction in functional kriging
Maria Franco-Villoria, Rosaria Ignaccolo
The increasing interest in spatially correlated functional data has led to the development of appropriate geostatistical techniques that allow to predict a curve at an unmonitored…
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…
Modeling threshold exceedance probabilities of spatially correlated time series
Dana Draghicescu, Rosaria Ignaccolo
The Commission of the European Union, as well the United States Environmental Protection Agency, have set limit values for some pollutants in the ambient air that have been shown t…