[Forum SIS] Seminario Emilio Porcu a Roma Tor Vergata

[Alessia Caponera]

Dear all,

I would like to announce the following talk that will be held on Thursday November 7th 2019, at 5 PM, in Aula D’Antoni of the Department of Mathematics, University of Rome Tor Vergata.

Speaker: Emilio Porcu (Trinity College Dublin)

Title: Modeling Temporally Evolving and Spatially Globally Dependent Data

Abstract: The last decades have seen an unprecedented increase in the
availability of data sets that are inherently global and temporally
evolving, from remotely sensed networks to climate model ensembles. This
paper provides an overview of statistical modeling techniques for
space–time processes, where space is the sphere representing our
planet. In particular, we make a distinction between (a) second
order‐based approaches and (b) practical approaches to modeling
temporally evolving global processes. The former approaches are based on
the specification of a class of space–time covariance functions, with
space being the two‐dimensional sphere. The latter are based on
explicit description of the dynamics of the space–time process, that
is, by specifying its evolution as a function of its past history with
added spatially dependent noise.
We focus primarily on approach (a), for which the literature has been
sparse. We provide new models of space–time covariance functions for
random fields defined on spheres cross time. Practical approaches (b)
are also discussed, with special emphasis on models built directly on
the sphere, without projecting spherical coordinates onto the plane.
We present a case study focused on the analysis of air pollution from
the 2015 wildfires in Equatorial Asia, an event that was classified as
the year's worst environmental disaster. The paper finishes with a list
of the main theoretical and applied research problems in the area, where
we expect the statistical community to engage over the next decade.

Kind regards,
Alessia Caponera
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