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Statistical Inference for Transformation Inhomogeneous Point Processes

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  • Linda Stougaard Nielsen
  • Eva B. Vedel Jensen

Abstract

. Statistical inference for exponential inhomogeneous Markov point processes by transformation is discussed. It is argued that the inhomogeneity parameter can be estimated, using a partial likelihood based on an inhomogeneous Poisson point process. The inhomogeneity parameter can thereby be estimated without taking the interaction into account, which simplifies the statistical analysis considerably. Data analysis and simulation experiments support the results.

Suggested Citation

  • Linda Stougaard Nielsen & Eva B. Vedel Jensen, 2004. "Statistical Inference for Transformation Inhomogeneous Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(1), pages 131-142, March.
    • Handle: RePEc:bla:scjsta:v:31:y:2004:i:1:p:131-142
    DOI: 10.1111/j.1467-9469.2004.00377.x
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    Cited by:

    1. Rajala, T. & Penttinen, A., 2014. "Bayesian analysis of a Gibbs hard-core point pattern model with varying repulsion range," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 530-541.
    2. Ute Hahn & Eva B. Vedel Jensen, 2016. "Hidden Second-order Stationary Spatial Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 455-475, June.

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