Validation of Statistical Models for Spatial Point Patterns

Details Validation of Statistical Models for Spatial Point Patterns Validation of Statistical Models for Spatial Point Patterns

Nov 2007

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007aspc..371...22b&link_type=abstract

Statistical Challenges in Modern Astronomy IV ASP Conference Series, Vol. 371, proceedings of the conference held 12-15 June 200

Astronomy and Astrophysics

Astronomy

Scientific paper

Statistical methods for analysing a spatial point pattern are reviewed and criticised, with emphasis on the statistical `validity' of the analysis. Three main approaches are to extract a numerical summary of the pattern (such as the pair correlation function), to search for interesting features (such as clusters), or to fit a statistical model to the pattern. We give a statistical critique of each approach, and describe recent improvements, such as inhomogeneous K-functions, LISA statistics, Cox models and model-fitting algorithms. The key question is how to check the `validity' of an analysis. We describe the new concept of residuals for a spatial point process, and its uses in model validation.

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