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Multi-dimensional Point Process Models in R

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  • Peng, Roger

Abstract

A software package for fitting and assessing multidimensional point process models using the R statistical computing environment is described. Methods of residual analysis based on random thinning are discussed and implemented. Features of the software are demonstrated using data on wildfire occurrences in Los Angeles County, California and earthquake occurrences in Northern California.

Suggested Citation

  • Peng, Roger, 2003. "Multi-dimensional Point Process Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i16).
    • Handle: RePEc:jss:jstsof:v:008:i16
    DOI: http://hdl.handle.net/10.18637/jss.v008.i16
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    References listed on IDEAS

    as
    1. Yosihiko Ogata, 1998. "Space-Time Point-Process Models for Earthquake Occurrences," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 50(2), pages 379-402, June.
    2. Schoenberg, Frederic, 1999. "Transforming spatial point processes into Poisson processes," Stochastic Processes and their Applications, Elsevier, vol. 81(2), pages 155-164, June.
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    Cited by:

    1. Adhitya Ronnie Effendie & Kariyam & Aisya Nugrafitra Murti & Marfelix Fernaldy Angsari & Gunardi, 2022. "Classifying Insurance Reserve Period via Claim Frequency Domain Using Hawkes Process," Risks, MDPI, vol. 10(11), pages 1-21, November.
    2. repec:jss:jstsof:08:i16 is not listed on IDEAS
    3. repec:jss:jstsof:35:i08 is not listed on IDEAS
    4. repec:jss:jstsof:12:i06 is not listed on IDEAS
    5. Lamprinakou, Stamatina & Barahona, Mauricio & Flaxman, Seth & Filippi, Sarah & Gandy, Axel & McCoy, Emma J., 2023. "BART-based inference for Poisson processes," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
    6. Baddeley, Adrian & Turner, Rolf, 2005. "spatstat: An R Package for Analyzing Spatial Point Patterns," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i06).

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