[Forum SIS] 2017 ABS Summer School

[Consonni Guido]

Please find below the announcement of the 14th edition of
the ABS (Applied Bayesian Statistics) Summer school on


          MODELING SPATIAL AND SPATIO-TEMPORAL DATA
               WITH  ENVIRONMENTAL APPLICATIONS

with Bruno SANSO', Professor of Statistics,
University of California Santa Cruz,  as lecturer.

Like in the past four years, the 2017 school will be held
in the magnificent Villa del Grumello, in Como (Italy),

on the Lake Como shore.


Guido Consonni and Fabrizio Ruggeri
ABS17 Directors
Raffaele Argiento
ABS17 Executive Director



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          *            ABS17            *
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        Applied Bayesian Statistics School

        MODELING SPATIAL AND SPATIO-TEMPORAL DATA
           WITH  ENVIRONMENTAL APPLICATIONS

          June 19-23, 2017

          Villa del Grumello, Como, Italy


Lecturer:

  Bruno Sanso', Professor of Statistics,
  University of California Santa Cruz
  https://users.soe.ucsc.edu/~bruno/



The conference webpage is

>>>>   web.mi.imati.cnr.it/conferences/abs17.html   <<<<


Registration is now open. Please note that the conference
room allows only for a  limited number of  participants.



The ABS17 Secretariat can be contacted at

                     abs17 at mi.imati.cnr.it




COURSE OUTLINE

This course is intended for students who have a

background in statistical methods and modeling. The

course is focused on models for data that are spatially

referenced and that evolve in time. We will develop

models for stochastic processes that are indexed at

irregularly scattered, fixed, locations. We will look

into the theoretical properties of those models as well

as into the computational issues involved in the

estimation of their parameters. We will extend the

analysis of fields of spatial observations that are

collected in time. In particular, we will consider

dynamically varying process where space and time

interact. Real-data applications of Bayesian methods with

MCMC techniques will be illustrated.

 Day 1: Introduction to Bayesian methods and hierarchical

models. Examples of spatially referenced data. Basic

properties of Gaussian random fields. Graphical

exploration of spatial fields.

 Day 2: Variograms. Examples of families of correlations

functions. Bayesian approach to estimation and prediction

of spatial random fields.

 Day 3: The big data problem: reduced rank models and

other modern approaches to dimension reduction.

 Day 4: Spatio-temporal models. Dynamic linear models:

integro-differential equations.

 Day 5: Extensions



PRACTICAL INFORMATION

The school will replicate the successful format of the

previous years, and will feature lectures and practical

sessions (run by a junior researcher), as well as

participants' talks. It will start on Monday after lunch

and end on Friday before lunch; Wednesday afternoon is

free. Accommodation is available either at the Villa

guesthouse or in downtown hotels (info will appear soon

on the website). Como can be easily reached by train from

Milan and its airports. More details are available on the

website.




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