In this paper, we describe the structure and the features of the air quality and meteorological
monitoring system adopted in the Lombardy region in Northern Italy. We are interested in …

As high-dimensional and high-frequency data are being collected on a large scale, the
development of new statistical models is being pushed forward. Functional data analysis …

Cokriging is a geostatistical technique that is used for spatial prediction when realizations of
a random field are available. If a secondary variable is cross-correlated with the primary …

Sign, Wilcoxon and Mann-Whitney tests are nonparametric methods in one or two-sample
problems. The nonparametric methods are alternatives used for testing hypothesis when the …

We review recent advances in Object Oriented Spatial Statistics, a system of ideas,
algorithms and methods that allows the analysis of high dimensional and complex data …

We propose a method for the analysis of functional data with complex dependencies, such
as spatially dependent curves or time dependent surfaces, over highly textured domains …

One of the core tasks in digital soil mapping (DSM) studies is the estimation of the spatial
distribution of different soil variables. In addition, however, assessing the uncertainty of …

Streamflow, as a natural phenomenon, is continuous in time and so are the meteorological
variables which influence its variability. In practice, it can be of interest to forecast the whole …

This paper is focus on spatial functional variables whose observations are a set of spatially
correlated sample curves obtained as realizations of a spatio-temporal stochastic process. In …

This is the editorial letter for the special issue dedicated to Spatial Functional Statistics,
motivated by the joint VII International Workshop on Spatio-temporal Modelling (METMAVII) …