8.
STOICA Radu radu.stoica@univ-lille1.fr
Universite de Lille, France
Titre: Spatial data analysis through probabilistic modelling and statistical inference (details)
Résumé:
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{\LARGE Spatial data analysis through probabilistic modelling and statistical inference}\\[.5in]
{\large R. S. Stoica \footnote{radu.stoica@univ-lille1.fr}}\\[.2in]
{\em Université de Lille, Laboratoire Paul Painlevé\\
59655 Villeneuve d'Ascq Cedex, France}\\[.1in]
{\em Institut de Mécanique Céleste et Calcul des Ephémérides\\
Observatoire de Paris, 75014 Paris, France}
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\noindent
Spatial data is made of elements having two components: position in an observation domain and characteristic measured or associated with the given position. In this presentation several examples of such data sets are showed: road networks evolution in forest exploitations, the gravity centre positions of a binary asteroid system, the coordinates of the artificial spatial debris around the Earth, the map of the planetary perturbations affecting the comets dynamics, the galaxy centres observed in a region of our Universe. The particulaor structure of the data, {\it i.e.} spatial coordinate and associate mark, induces that the question almost always arising in such a data analysis is what is the pattern hidden in the data? The answers to this type of questions may be given using methodology based on probabilistic and statistical theory: summary statistics, modelling, MCMC simulation, statistical inference and results evaluation. A brief presentation of some of these tools, especially adapted for the application on the previously cited examples, it will be given.\\
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