The following PhD course in Geostatistics will be held at the
Department of Mathematics, Politecnico di Milano
The course covers classical and advanced models and methods for the
statistical analysis of data with spatial dependence. Lectures
include tutorial sessions with the software R. Many case studies
will be presented, with applications in the earth-sciences, in the
neurosciences and more generally in the life-sciences (including
medical imaging), and in the engineering.
Lessons:
1 & 2) Kriging: stationary and isotropic random fields;
structural properties of the variogram; valid variogram models;
variogram estimation; kriging prediction for georeferenced data;
drift estimation; kriging for data in Hilbert spaces. Lecturer: A.
Menafoglio.
3) Non-parametric techniques. Lecturer: Simone Vantini.
4) Bayesian models for georeferenced data and areal data. Lecturer:
A. Guglielmi.
5) Numerical methods for the analysis of spatially distributed data:
thin-plate splines; tensor product splines. Lecturer: L. Sangalli.
6) Spatial regression with differential regularization. Lecturer: L.
Sangalli.
Essential bibliography:
- N. Cressie. Statistics for Spatial data. John Wiley & Sons,
New York, 1993.
- S. Banerjee, B. P. Carlin, and A. E. Gelfand. Hierarchical
Modeling and Analysis for Spatial Data. Chapman & Hall / CRC,
2004.
- R. Bivand, E. Pebesma, V. Gomez-Rubio. Applied Spatial Data
Analysis with R. Springer, 2008
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Laura Maria Sangalli
MOX - Dipartimento di Matematica
Politecnico di Milano
Piazza Leonardo da Vinci 32
20133 Milano - Italy
tel: +39 02 2399 4554
fax: +39 02 2399 4568
email: laura.sangalli@polimi.it
url: http://mox.polimi.it/~sangalli