Adapting to climate change as a consequence of increasing greenhouse gas (GHG)
emissions is of paramount importance in the near future. Therefore, recognition of spatial …

Several methods have been proposed in the spatial statistics literature to analyse big data
sets in continuous domains. However, new methods for analysing high-dimensional areal …

This article proposes a physical-statistical modeling approach for spatio-temporal data
arising from a class of stochastic convection-diffusion processes. Such processes are widely …

Boosting Trees are one of the most successful statistical learning approaches that involve
sequentially growing an ensemble of simple regression trees (“weak learners”). This paper …

The article presents a methodology for supervised regionalization of data on a spatial
domain. Defining a spatial process at multiple scales leads to the famous ecological fallacy …

Geostationary weather satellites collect high‐resolution data comprising a series of images.
The Derived Motion Winds (DMW) Algorithm is commonly used to process these data and …

Boosting Trees are one of the most successful statistical learning approaches that involve
sequentially growing an ensemble of simple regression trees (ie," weak learners"). However …