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Simulated annealing and object point processes: Tools for analysis of spatial patterns

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  • Stoica, R.S.
  • Gregori, P.
  • Mateu, J.

Abstract

This paper introduces a three-dimensional object point process--the Bisous model--that can be used as a prior for three-dimensional spatial pattern analysis. Maximization of likelihood or penalized-likelihood functions based on this model requires global optimization techniques, such as the simulated annealing algorithm. Theoretical properties of the model are discussed and the convergence of the proposed optimization method is proved. Finally, a simulation study is presented.

Suggested Citation

  • Stoica, R.S. & Gregori, P. & Mateu, J., 2005. "Simulated annealing and object point processes: Tools for analysis of spatial patterns," Stochastic Processes and their Applications, Elsevier, vol. 115(11), pages 1860-1882, November.
    • Handle: RePEc:eee:spapps:v:115:y:2005:i:11:p:1860-1882
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    References listed on IDEAS

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    1. A. Pievatolo & P. J. Green, 1998. "Boundary detection through dynamic polygons," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(3), pages 609-626.
    2. Bruce Hajek, 1988. "Cooling Schedules for Optimal Annealing," Mathematics of Operations Research, INFORMS, vol. 13(2), pages 311-329, May.
    3. M. N. M. Van Lieshout & R. S. Stoica, 2003. "The Candy model: properties and inference," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(2), pages 177-206, May.
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    Cited by:

    1. Radu S. Stoica & Vicent J. Martínez & Enn Saar, 2007. "A three‐dimensional object point process for detection of cosmic filaments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(4), pages 459-477, August.

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