Summer School on Topics in Space-Time Modeling and Inference

Sunday 26 May will be arrival day. The scientific programme starts on Monday morning 27 May and ends on Friday 31 May around noon.


PhD-students and postdocs with an interest in spatial statistics.


Professor Peter J. Diggle, Lancaster University

Professor Tilmann Gneiting, University of Heidelberg

Professor Peter F. Craigmile, University of Glasgow

Professor Rasmus P. Waagepetersen, Aalborg University

Scope of the Summer School

Professor J. Peter Diggle, Lancaster University, will give a simple classification of space-time point processes and/or data according to whether the spatial or temporal dimension (but not both!) is discrete, and argue that these different situations require different approaches to statistical analysis, and that the choice of modelling strategy should be influenced by the scientific goals of the study that generated the data for analysis. He will also describe statistical models, methods and R packages for space-time point process data.
Professor Tilmann Gneiting, University of Heidelberg, will discuss the correlation theory of stochastic processes on Euclidean domains and spheres, which offers a wide range of challenging open problems. Applications and case studies in weather and climate research call for an increased involvement of probabilists and statisticians in the atmospheric sciences.
Professor Peter F. Craigmile, University of Glasgow, will introduce spectral- and wavelet-based methods that can be applied to temporal, spatial, and spatiotemporal data. Topics include time-frequency representations, model construction, and approximate methods of inferences for spatio-temporal processes.
Professor Rasmus P. Waagepetersen, Aalborg University, will consider statistical models and methods for spatial point processes. His lectures will provide an introduction to spatial Gibbs and Cox point processes and to various approaches to inference for spatial point processes including summary statistics, estimating functions and maximum likelihood estimation.

The mode of presentations will be a combination of lectures, software demonstration and, for those who have their own computers loaded with the R software, opportunities to try the methods for themselves.


Professor Jesper Møller, Department of Mathematical Sciences, Aalborg University, in collaboration with CSGB.


Morning sessions (Monday-Friday): 09:00-11:00, 11:30-12:30.

Coffee/tea/water and fruit in the break 11:00-11:30. The lecturers decide if and when further breaks should occur.

Lunch 12:30-13:30:

Monday, Tuesday, and Thursday: Buffet and soft drink, the canteen at Novi.

Wednesday and Friday: Sandwich and soft drink, Department of Mathematical Sciences, Aalborg University.

Afternoon sessions (Monday, Tuesday, Thursday): 13:30-15:30, 16:00-17:00.

Coffee/tea/water and cake in the break 15:30-16:00. The lecturers decide if and when further breaks should occur.

Monday 27 May (6 hours)
Professor Tilman Gneiting: Covariance models for spatial and space-time data.

Tuesday 28 May (6 hours)
Professor Peter Craigmile: Time-frequency methods for spatio-temporal data.

Wednesday 29 May morning (3 hours) and Thursday 30 May morning (3 hours).

Professor Rasmus Waagepetersen: Statistical models and methods for spatial point processes.

Thursday 30 May afternoon (3 hours) and Friday 31 May morning (3 hours).
Professor Peter Diggle: Statistical models and methods for space-time point processes.
Poster session: Tuesday at Aalborg University. After Peter Craigmile's lectures (and a break), 5 minutes/short presentations of all posters followed by a poster session together with a buffet and wines, soft drinks and water.
Social events: Monday 27 May: Dinner at a restaurant in Aalborg.
Wednesday 29 May at 13:30-22:30: Excursion to Skagen including dinner with drinks at Restaurant Pakhuset.

Deadline for registration

1 February 2013.


PhD ECTS: You will get 2.5 ECTS for participating. You can get additional 2.5 ECTS if you present a poster at the summer school and write a small report on how the topics covered in the course relate to your own PhD project. That is in total you can get 5 ECTS points.

Supported by the Danish Council for Independent Research | Natural Sciences, Grant 12-124675, "Mathematical and Statistical Analysis of Spatial Data", and the Villum Foundation.