PhD course in Aalborg

On 21-22 April 2015 Adrian Baddeley will give a two day PhD course at Aalborg University titled Analysing spatial point patterns with R. The course has a strong focus on hands-on exercises using the comprehensive R package spatstat. No prior knowledge about spatial statistics is required, but basic familiarity with R and ordinary statistical concepts are needed.

For further information read the course description below or contact course organizer Ege Rubak (rubak@math.aau.dk). You have to sign up for the course before 1 April by logging on to phd.moodle.aau.dk (you need to create a login if you aren’t affiliated with AAU).

Description:

Spatial point pattern datasets are becoming more common across many fields of research. However, statistical methodology for analysing these data has not been widely disseminated. This course is a practical introduction to the analysis of spatial point patterns with a strong focus on hands-on exercises throughout the course. The course gives an in-depth introduction to spatstat, which is an R-package for analysing spatial point patterns. The package supports a complete statistical analysis of spatial point pattern data: data input and inspection, calculations, plotting, exploratory data analysis, hypothesis tests, model-fitting, simulation, Monte Carlo methods and model diagnostics. The course will treat all these subjects, and in particular the goals are for the participants to:

• Understand basic statistical concepts used in spatial point pattern analysis.
• Get an overview of the capabilities of spatstat and how to find your way around.
  
• Learn how to conduct a basic analysis of a point pattern dataset:
  • Calculating and plotting exploratory summaries.
  • Fitting Poisson, Cox, and Gibbs point process models.
  • Validating and critiquing fitted models.

To obtain these goals we:

• begin with real examples and establish basic principles.
• introduce relevant graphical/exploratory methods including non-parametric intensity estimation, pair correlation, Ripley’s K-function.
• demonstrate model building, model-fitting, formal inference and model validation.

Prerequisites

• Basic familiarity with R.
• Basic familiarity with statistical concepts.
• Please bring your own laptop, with the latest version of R and spatstat installed. Please ensure that all the ‘Suggested’ packages for spatstat are also installed.

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Organizer: Assistant Professor Ege Rubak, e-mail: rubak@math.aau.dk
Lecturer: Professor Adrian Baddeley, Curtin University
ECTS: 1
Dates: 21-22 April 2015
Hours: 9:00-12:00 and 13:00-16:00 both days
Place: Aalborg University, Fredrik Bajers Vej 7G, Room G5-112
Number of seats: 40
Deadline: 1 April 2015