Analysing spatial point patterns with R (2015)

Welcome to Analysing Spatial Point Patterns with R


 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.
  • 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


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.

Organizer: Assistant Professor Ege Rubak, e-mail: rubak@math.aau.dk
Lecturers: Professor Adrian Baddeley, Curtin University
ECTS: 1
Time: 21-22 April, 2015
Place: Aalborg University, Fredrik Bajers Vej 7G, Room G5-112 Zip code: 9220
City: Aalborg Number of seats: 40
Deadline: 1 April 2015