IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v115y2005i11p1860-1882.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4149(05)00083-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. Bruce Hajek, 1988. "Cooling Schedules for Optimal Annealing," Mathematics of Operations Research, INFORMS, vol. 13(2), pages 311-329, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. C. P. Stephens & W. Baritompa, 1998. "Global Optimization Requires Global Information," Journal of Optimization Theory and Applications, Springer, vol. 96(3), pages 575-588, March.
    2. George Kapetanios, 2005. "Variable Selection using Non-Standard Optimisation of Information Criteria," Working Papers 533, Queen Mary University of London, School of Economics and Finance.
    3. Souvik Das & Ashwin Aravind & Ashish Cherukuri & Debasish Chatterjee, 2022. "Near-optimal solutions of convex semi-infinite programs via targeted sampling," Annals of Operations Research, Springer, vol. 318(1), pages 129-146, November.
    4. Pirlot, Marc, 1996. "General local search methods," European Journal of Operational Research, Elsevier, vol. 92(3), pages 493-511, August.
    5. Steinhofel, K. & Albrecht, A. & Wong, C. K., 1999. "Two simulated annealing-based heuristics for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 118(3), pages 524-548, November.
    6. Löwe, Matthias, 1997. "On the invariant measure of non-reversible simulated annealing," Statistics & Probability Letters, Elsevier, vol. 36(2), pages 189-193, December.
    7. Miclo, Laurent, 1995. "Remarques sur l'ergodicité des algorithmes de recuit simulé sur un graphe," Stochastic Processes and their Applications, Elsevier, vol. 58(2), pages 329-360, August.
    8. Kapetanios, George, 2006. "Cluster analysis of panel data sets using non-standard optimisation of information criteria," Journal of Economic Dynamics and Control, Elsevier, vol. 30(8), pages 1389-1408, August.
    9. Antonio Jiménez-Martín & Alfonso Mateos & Josefa Z. Hernández, 2021. "Aluminium Parts Casting Scheduling Based on Simulated Annealing," Mathematics, MDPI, vol. 9(7), pages 1-18, March.
    10. Van Buer, Michael G. & Woodruff, David L. & Olson, Rick T., 1999. "Solving the medium newspaper production/distribution problem," European Journal of Operational Research, Elsevier, vol. 115(2), pages 237-253, June.
    11. Zhang Lihao & Ye Zeyang & Deng Yuefan, 2019. "Parallel MCMC methods for global optimization," Monte Carlo Methods and Applications, De Gruyter, vol. 25(3), pages 227-237, September.
    12. Yiyo Kuo, 2014. "Design method using hybrid of line-type and circular-type routes for transit network system optimization," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 600-613, July.
    13. Broekmeulen, Rob A. C. M. & van Weert, Arjen & Saedt, Anton P. H., 2002. "Comparing three alternative optimisation methods for the treatment planning of bulbs," Agricultural Systems, Elsevier, vol. 72(1), pages 59-71, April.
    14. F. R. B. Cruz & A. R. Duarte & G. L. Souza, 2018. "Multi-objective performance improvements of general finite single-server queueing networks," Journal of Heuristics, Springer, vol. 24(5), pages 757-781, October.
    15. Rodriguez-Tello, Eduardo & Hao, Jin-Kao & Torres-Jimenez, Jose, 2008. "An improved simulated annealing algorithm for bandwidth minimization," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1319-1335, March.
    16. Doole, Graeme J., 2007. "A primer on implementing compressed simulated annealing for the optimisation of a constrained simulation model in Microsoft Excel," Working Papers 7420, University of Western Australia, School of Agricultural and Resource Economics.
    17. Peters, G.W. & Sisson, S.A. & Fan, Y., 2012. "Likelihood-free Bayesian inference for α-stable models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3743-3756.
    18. Sam Hui & Eric Bradlow, 2012. "Bayesian multi-resolution spatial analysis with applications to marketing," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 419-452, December.
    19. Zhao, Fang & Zeng, Xiaogang, 2008. "Optimization of transit route network, vehicle headways and timetables for large-scale transit networks," European Journal of Operational Research, Elsevier, vol. 186(2), pages 841-855, April.
    20. Gabriel M. Portal & Marcus Ritt & Leonardo M. Borba & Luciana S. Buriol, 2016. "Simulated annealing for the machine reassignment problem," Annals of Operations Research, Springer, vol. 242(1), pages 93-114, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:spapps:v:115:y:2005:i:11:p:1860-1882. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/505572/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.