Statistical Analysis for Space-Time Data

15/07/2019 a 17/07/2019 Faculdade de Ciências da Universidade de Lisboa SPE, SEIO

Statistical Analysis for Space-Time Data

July 15-17, 2019 – Lisboa, Portugal

The European Courses in Advanced Statistics on Statistical Analysis for Space-Time Data (ECAS2019) is organized by the Portuguese Statistical Society (SPE) and the Spanish Society of Statistics and Operational Research (SEIO) and will take place in Lisbon, Portugal, on July 15th-17th, 2019.

The ECAS courses are intended to achieve postgraduate training in special areas of statistics for (especially 1st year) PhD students, researchers, teachers at universities, and professionals interested in the application of new statistical methods.

Overview

Due to the proliferation of data sets that are both spatially and temporally indexed, spatio-temporal modelling has received an increasing attention in the last few years. Space-Time data are usually related to applied areas, such as environmental and health sciences, and their analyses focus, namely, on:

  1. reading, visualizing, and analysing spatial data, where observations can be identified with geographical locations;
  2. generating hypotheses for further ecological or epidemiological study;
  3. producing a smoothed map, identifying spatial and temporal trends;
  4. formulating policy decisions related to certain disease over space and time.

The invited lecturers will present their methodological advancements with a heavy emphasis on applications. A poster session with contributed papers will complement the scientific program (although any participant can attend the courses without the presentation of a poster).

Lecturers

Adrian Baddeley, Curtin University – Australia,

Spatial Point Patterns: Methodology and Applications with R expand_more

 

Patrick Brown, St. Michael's Hospital and University of Toronto – Canada

Statistical models and inference for spatio-temporal areal data expand_more

 

Håvard Rue, KAUST – Saudi Arabia,

Spatial and spatio-temporal models using the SPDE-approach expand_more

 

Liliane Bel, AgroParisTech – France,

New trends in spatio-temporal geostatistics

 

Scientific committee

Giovani Silva, IST, Universidade de Lisboa

Raquel Menezes, DMA, Universidade do Minho

Maria Eduarda Silva, FEP, Universidade do Porto

María Dolores Ugarte, Universidad Pública de Navarra

Rubén Fernández Casal, DM, Universidade da Coruña

Ricardo Cao, DM, Universidade da Coruña

 

Organizing committee

Isabel Natário, FCT, Univ. Nova de Lisboa

Paulo Soares, IST, Universidade de Lisboa

Soraia Pereira, FCUL, Universidade de Lisboa

Tomás Goicoa, Universidad Pública de Navarra

Anabel Forte, Universitat de València

Giovani Silva, IST, Universidade de Lisboa


mais informações

Edited/published: 18/03/2019