On Fitting Non-Stationary Markov Point Process Models on GLIM

  • A. B. Lawson
Conference paper

Abstract

The possibility of fitting general non-stationary point process models on GLIM is considered. Of primary concern is the possibility of using pseudoliklihood to obtain parameter estimates for a spatial Markov process model applied to the colonisation of plants. Extension of the method to fitting cluster/Cox process models is also considered.

Keywords

Conditional Intensity Mean Integrate Square Error Spatial Point Pattern Interpoint Distance Obtain Parameter Estimate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • A. B. Lawson
    • 1
  1. 1.Department of Mathematical and Computer SciencesDundee Institute of TechnologyDundeeUK

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