Statistical analysis of complex and spatially dependent data: a review of Object Oriented Spatial Statistics

Keywords

Statistical learning
Code:
34/2016
Title:
Statistical analysis of complex and spatially dependent data: a review of Object Oriented Spatial Statistics
Date:
Thursday 6th October 2016
Author(s):
Menafoglio, A.; Secchi, P.
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Abstract:
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 when their spatial dependence is an important issue. At the intersection of different disciplines -- including mathematics, statistics, computer science and engineering -- Object Oriented Spatial Statistics provides the right perspective to address key problems in varied contexts, from Earth and life sciences to urban planning. We illustrate a few paradigmatic methods applied to problems of prediction, classification and smoothing, giving emphasis to the key ideas Object Oriented Spatial Statistics relies upon.
This report, or a modified version of it, has been also submitted to, or published on
European Journal of Operational Research