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Second‐order analysis of inhomogeneous spatio‐temporal point process data

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  • Edith Gabriel
  • Peter J. Diggle

Abstract

Second‐order methods provide a natural starting point for the analysis of spatial point process data. In this note we extend to the spatio‐temporal setting a method proposed by Baddeley et al. [Statistica Neerlandica (2000) Vol. 54, pp. 329–350] for inhomogeneous spatial point process data, and apply the resulting estimator to data on the spatio‐temporal distribution of human Campylobacter infections in an area of north‐west England.

Suggested Citation

  • Edith Gabriel & Peter J. Diggle, 2009. "Second‐order analysis of inhomogeneous spatio‐temporal point process data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(1), pages 43-51, February.
    • Handle: RePEc:bla:stanee:v:63:y:2009:i:1:p:43-51
    DOI: 10.1111/j.1467-9574.2008.00407.x
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    References listed on IDEAS

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    1. 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.
    2. Martin Kulldorff & Ulf Hjalmars, 1999. "The Knox Method and Other Tests for Space-Time Interaction," Biometrics, The International Biometric Society, vol. 55(2), pages 544-552, June.
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    Cited by:

    1. Michaela Prokešová & Jiří Dvořák, 2014. "Statistics for Inhomogeneous Space-Time Shot-Noise Cox Processes," Methodology and Computing in Applied Probability, Springer, vol. 16(2), pages 433-449, June.
    2. 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.
    3. Jesper Møller & Farzaneh Safavimanesh & Jakob Gulddahl Rasmussen, 2016. "The cylindrical $K$-function and Poisson line cluster point processes," Biometrika, Biometrika Trust, vol. 103(4), pages 937-954.
    4. D'Angelo, Nicoletta & Adelfio, Giada & Mateu, Jorge, 2023. "Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
    5. Ghorbani, Mohammad & Vafaei, Nafiseh & Dvořák, Jiří & Myllymäki, Mari, 2021. "Testing the first-order separability hypothesis for spatio-temporal point patterns," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    6. O. Cronie & M. N. M. Van Lieshout, 2015. "A J -function for Inhomogeneous Spatio-temporal Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 562-579, June.
    7. Eckardt, Matthias & González, Jonatan A. & Mateu, Jorge, 2021. "Graphical modelling and partial characteristics for multitype and multivariate-marked spatio-temporal point processes," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    8. C. Comas & F. J. Rodriguez-Cortes & J. Mateu, 2015. "Second-order analysis of anisotropic spatiotemporal point process data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(1), pages 49-66, February.
    9. Jiří Dvořák & Michaela Prokešová, 2016. "Parameter Estimation for Inhomogeneous Space-Time Shot-Noise Cox Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 939-961, December.
    10. Nicoletta D’Angelo & Giada Adelfio, 2024. "Minimum contrast for the first-order intensity estimation of spatial and spatio-temporal point processes," Statistical Papers, Springer, vol. 65(6), pages 3651-3679, August.
    11. Arbia, Giuseppe & Espa, Giuseppe & Giuliani, Diego & Dickson, Maria Michela, 2014. "Spatio-temporal clustering in the pharmaceutical and medical device manufacturing industry: A geographical micro-level analysis," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 298-304.
    12. Edith Gabriel, 2014. "Estimating Second-Order Characteristics of Inhomogeneous Spatio-Temporal Point Processes," Methodology and Computing in Applied Probability, Springer, vol. 16(2), pages 411-431, June.
    13. Arbia, G. & Espa, G. & Giuliani, D. & Mazzitelli, A., 2012. "Clusters of firms in an inhomogeneous space: The high-tech industries in Milan," Economic Modelling, Elsevier, vol. 29(1), pages 3-11.
    14. Ottmar Cronie & Julia Jansson & Konstantinos Konstantinou, 2024. "Discussion of the Paper “Marked Spatial Point Processes: Current State and Extensions to Point Processes on Linear Networks”," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(2), pages 379-388, June.
    15. Nicoletta D’Angelo & Giada Adelfio & Jorge Mateu, 2023. "Local inhomogeneous second-order characteristics for spatio-temporal point processes occurring on linear networks," Statistical Papers, Springer, vol. 64(3), pages 779-805, June.

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