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Case Studies in Spatial Point Process Modeling pp 23–74Cite as

Modelling Spatial Point Patterns in R

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Part of the Lecture Notes in Statistics book series (LNS,volume 185)

Summary

We describe practical techniques for fitting stochastic models to spatial point pattern data in the statistical package R. The techniques have been implemented in our package spatstat in R. They are demonstrated on two example datasets.

Key words

  • EDA for spatial point processes
  • Point process model fitting and simulation
  • R
  • Spatstat package

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Author information

Authors and Affiliations

  1. School of Mathematics and Statistics, University of Western Australia, Crawley, 6009, WA, Australia

    Adrian Baddeley

  2. Department of Mathematics and Statistics, University of New Brunswick, Fredericton, N.B., E3B 5A3, Canada

    Rolf Turner

Authors
  1. Adrian Baddeley
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  2. Rolf Turner
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Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Western Australia, Nedlands, 6907, Australia

    Adrian Baddeley

  2. Department of Mathematics, Universitat Jaume 1 of Castellon, Castellon, 12071, Spain

    Pablo Gregori & Jorge Mateu & 

  3. INRA - Biometrie, Domaine St. Paul, Site Agroparc, 84914, Avignon, Cedex 9, France

    Radu Stoica

  4. Institut für Stochastik, TU Bergakademie Freiberg, Prüferstraße 9, D-09596, Freiberg, Germany

    Dietrich Stoyan

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Baddeley, A., Turner, R. (2006). Modelling Spatial Point Patterns in R. In: Baddeley, A., Gregori, P., Mateu, J., Stoica, R., Stoyan, D. (eds) Case Studies in Spatial Point Process Modeling. Lecture Notes in Statistics, vol 185. Springer, New York, NY. https://doi.org/10.1007/0-387-31144-0_2

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