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