1-5 June 2011 at Sandbjerg Estate, Sønderborg.

The programme starts at 3 pm on Wednesday June 1 and ends around noon on Sunday June 5.

Data which record the spatial locations of events (such as crimes, disease
cases, meteorite impacts) or objects (trees, nests, galaxies, cells) can be regarded as spatial patterns of points. This course presents statistical methodology for analysing spatial point patterns, and its practical implementation in the statistical package R. In the course, we will learn to use `spatstat', an add-on library for spatial statistics in R.
The course will feature theoretical presentations, software demonstrations and hands-on practical exercises. Participants should bring a laptop for the exercises.

• Statistical formulation and methodological issues
• Data input and handling
• Exploratory analysis
• Nonparametric intensity estimation
• Distance methods and summary statistics such as Ripley's K function
• Point process models (Poisson, Gibbs, Cox, cluster)
• Likelihood, pseudolikelihood and Bayesian inference
• Model validation
• Simulation techniques
• Multitype and marked point patterns
• Inhomogeneous point processes

• Adrian Baddeley (Perth)
• Yongtao Guan (Yale)
• Ute Hahn (Aarhus)
• Jakob Gulddahl Rasmussen (Aalborg)
• Ege Rubak (Aalborg)
• Rasmus Waagepetersen (Aalborg)

Please click here for the programme.