3 papers
stat.ME2026
Predicting disease severity and large-scale spread from coupled severity measurements and imperfect indicators: Application to beet yellows
Baptiste Oger, César Martinez, François Joudelat +2
Whether in human, animal, or plant health, effective disease management requires the ability to characterize disease dynamics across space and time. In this context, integrating in…
stat.AP2026
A Two-Step Spatio-Temporal Framework for Turbine-Height Wind Estimation at Unmonitored Sites from Sparse Meteorological Data
Eamonn Organ, Maeve Upton, Denis Allard +2
Accurate estimates of wind speeds at wind turbine hub heights are crucial for both wind resource assessment and day-to-day management of electricity grids with high renewable penet…
stat.AP2026
Enhancing the Accuracy of Spatio-Temporal Models for Wind Speed Prediction by Incorporating Bias-Corrected Crowdsourced Data
Eamonn Organ, Maeve Upton, Denis Allard +2
Accurate high-resolution spatial and temporal wind speed data is critical for estimating the wind energy potential of a location. For real-time wind speed prediction, statistical m…