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Structured Spatio‐Temporal Shot‐Noise Cox Point Process Models, with a View to Modelling Forest Fires

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  • JESPER MØLLER
  • CARLOS DÍAZ‐AVALOS

Abstract

. Spatio‐temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot‐noise process, are considered. Such models are flexible and tractable for statistical analysis, using spatio‐temporal versions of intensity and inhomogeneous K‐functions, quick estimation procedures based on composite likelihoods and minimum contrast estimation, and easy simulation techniques. These advantages are demonstrated in connection with the analysis of a relatively large data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio‐temporal log‐Gaussian Cox point process model, and likelihood‐based methods are discussed to some extent.

Suggested Citation

  • Jesper Møller & Carlos Díaz‐Avalos, 2010. "Structured Spatio‐Temporal Shot‐Noise Cox Point Process Models, with a View to Modelling Forest Fires," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(1), pages 2-25, March.
    • Handle: RePEc:bla:scjsta:v:37:y:2010:i:1:p:2-25
    DOI: 10.1111/j.1467-9469.2009.00670.x
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    References listed on IDEAS

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