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Structured Space-Sphere Point Processes and K-Functions

Author

Listed:
  • Jesper Møller

    (Aalborg University)

  • Heidi S. Christensen

    (Aalborg University)

  • Francisco Cuevas-Pacheco

    (Aalborg University)

  • Andreas D. Christoffersen

    (Aalborg University)

Abstract

This paper concerns space-sphere point processes, that is, point processes on the product space of ℝ d $\mathbb {R}^{d}$ (the d-dimensional Euclidean space) and S k $\mathbb {S}^{k}$ (the k-dimensional sphere). We consider specific classes of models for space-sphere point processes, which are adaptations of existing models for either spherical or spatial point processes. For model checking or fitting, we present the space-sphere K-function which is a natural extension of the inhomogeneous K-function for point processes on ℝ d $\mathbb {R}^{d}$ to the case of space-sphere point processes. Under the assumption that the intensity and pair correlation function both have a certain separable structure, the space-sphere K-function is shown to be proportional to the product of the inhomogeneous spatial and spherical K-functions. For the presented space-sphere point process models, we discuss cases where such a separable structure can be obtained. The usefulness of the space-sphere K-function is illustrated for real and simulated datasets with varying dimensions d and k.

Suggested Citation

  • Jesper Møller & Heidi S. Christensen & Francisco Cuevas-Pacheco & Andreas D. Christoffersen, 2021. "Structured Space-Sphere Point Processes and K-Functions," Methodology and Computing in Applied Probability, Springer, vol. 23(2), pages 569-591, June.
  • Handle: RePEc:spr:metcap:v:23:y:2021:i:2:d:10.1007_s11009-019-09712-w
    DOI: 10.1007/s11009-019-09712-w
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    References listed on IDEAS

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    1. Mari Myllymäki & Tomáš Mrkvička & Pavel Grabarnik & Henri Seijo & Ute Hahn, 2017. "Global envelope tests for spatial processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(2), pages 381-404, March.
    2. Jesper Møller & Mohammad Ghorbani, 2012. "Aspects of second-order analysis of structured inhomogeneous spatio-temporal point processes," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(4), pages 472-491, November.
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    4. Frédéric Lavancier & Jesper Møller & Ege Rubak, 2015. "Determinantal point process models and statistical inference," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 77(4), pages 853-877, September.
    5. Guan, Yongtao, 2006. "A Composite Likelihood Approach in Fitting Spatial Point Process Models," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1502-1512, December.
    6. Jesper Møller & Rasmus P. Waagepetersen, 2007. "Modern Statistics for Spatial Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 643-684, December.
    7. A. J. Baddeley & J. Møller & R. Waagepetersen, 2000. "Non‐ and semi‐parametric estimation of interaction in inhomogeneous point patterns," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 54(3), pages 329-350, November.
    8. Rasmus Plenge Waagepetersen, 2007. "An Estimating Function Approach to Inference for Inhomogeneous Neyman–Scott Processes," Biometrics, The International Biometric Society, vol. 63(1), pages 252-258, March.
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