IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v51y2007i8p3679-3688.html
   My bibliography  Save this article

An adjustment for edge effects using an augmented neighborhood model in the spatial auto-logistic model

Author

Listed:
  • Lim, Johan
  • Wang, Xinlei
  • Sherman, Michael

Abstract

No abstract is available for this item.

Suggested Citation

  • Lim, Johan & Wang, Xinlei & Sherman, Michael, 2007. "An adjustment for edge effects using an augmented neighborhood model in the spatial auto-logistic model," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3679-3688, May.
    • Handle: RePEc:eee:csdana:v:51:y:2007:i:8:p:3679-3688
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(06)00481-6
    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. Fuchun Huang & Yosihiko Ogata, 2002. "Generalized Pseudo-Likelihood Estimates for Markov Random Fields on Lattice," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 54(1), pages 1-18, March.
    2. Francesco Bartolucci, 2002. "A recursive algorithm for Markov random fields," Biometrika, Biometrika Trust, vol. 89(3), pages 724-730, August.
    3. R. Reeves, 2004. "Efficient recursions for general factorisable models," Biometrika, Biometrika Trust, vol. 91(3), pages 751-757, September.
    4. Anselin, Luc & Tam Cho, Wendy K., 2002. "Spatial Effects and Ecological Inference," Political Analysis, Cambridge University Press, vol. 10(3), pages 276-297, July.
    Full references (including those not matched with items on IDEAS)

    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. Magnussen, Steen & Reeves, Rob, 2008. "A method for bias-reduction of sample-based MLE of the autologistic model," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 103-111, September.
    2. Cécile Hardouin & Xavier Guyon, 2014. "Recursions on the marginals and exact computation of the normalizing constant for Gibbs processes," Computational Statistics, Springer, vol. 29(6), pages 1637-1650, December.
    3. Wanchuang Zhu & Yanan Fan, 2023. "A synthetic likelihood approach for intractable markov random fields," Computational Statistics, Springer, vol. 38(2), pages 749-777, June.
    4. Lim, Johan & Lee, Kiseop & Yu, Donghyeon & Liu, Haiyan & Sherman, Michael, 2012. "Parameter estimation in the spatial auto-logistic model with working independent subblocks," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4421-4432.
    5. Nial Friel & Håvard Rue, 2007. "Recursive computing and simulation-free inference for general factorizable models," Biometrika, Biometrika Trust, vol. 94(3), pages 661-672.
    6. Rulloni, Valeria, 2014. "Uniqueness condition for an auto-logistic model," Statistics & Probability Letters, Elsevier, vol. 87(C), pages 1-6.
    7. Breandán Ó'hUallacháin, 2008. "Regional growth transition clubs in the United States," Papers in Regional Science, Wiley Blackwell, vol. 87(1), pages 33-53, March.
    8. Cem Ertur & Julie Le Gallo & Catherine Baumont, 2006. "The European Regional Convergence Process, 1980-1995: Do Spatial Regimes and Spatial Dependence Matter?," International Regional Science Review, , vol. 29(1), pages 3-34, January.
    9. Solaiman Afroughi & Soghrat Faghihzadeh & Majid Jafari Khaledi & Mehdi Ghandehari Motlagh & Ebrahim Hajizadeh, 2011. "Analysis of clustered spatially correlated binary data using autologistic model and Bayesian method with an application to dental caries of 3--5-year-old children," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2763-2774, February.
    10. Martinelli, Gabriele & Eidsvik, Jo & Hauge, Ragnar, 2013. "Dynamic decision making for graphical models applied to oil exploration," European Journal of Operational Research, Elsevier, vol. 230(3), pages 688-702.
    11. Rimstad, Kjartan & Omre, Henning, 2013. "Approximate posterior distributions for convolutional two-level hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 187-200.
    12. Francesco Bartolucci & Alessio Farcomeni, 2010. "A note on the mixture transition distribution and hidden Markov models," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(2), pages 132-138, March.
    13. Cai, Bo & Dunson, David B., 2007. "Bayesian Multivariate Isotonic Regression Splines: Applications to Carcinogenicity Studies," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1158-1171, December.
    14. Judge, George G. & Miller, Douglas J. & Cho, Wendy K. T., 2003. "An Information Theoretic Approach to Ecological Estimation and Inference," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt7h03r00q, Department of Agricultural & Resource Economics, UC Berkeley.
    15. N. Friel & A. N. Pettitt, 2008. "Marginal likelihood estimation via power posteriors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(3), pages 589-607, July.
    16. Zachary Elkins & Beth Simmons, 2005. "On Waves, Clusters, and Diffusion: A Conceptual Framework," The ANNALS of the American Academy of Political and Social Science, , vol. 598(1), pages 33-51, March.
    17. Judge, George G. & Miller, Douglas J. & Cho, Wendy K. T., 2003. "An Information Theoretic Approach to Ecological Estimation and Inference," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt7h03r00q, Department of Agricultural & Resource Economics, UC Berkeley.
    18. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    19. Baodong Liu, 2007. "EI Extended Model and the Fear of Ecological Fallacy," Sociological Methods & Research, , vol. 36(1), pages 3-25, August.
    20. Longhi, Simonetta & Nijkamp, Peter, 2006. "Forecasting regional labor market developments under spatial heterogeneity and spatial correlation," Serie Research Memoranda 0015, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    More about this item

    Statistics

    Access and download statistics

    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:csdana:v:51:y:2007:i:8:p:3679-3688. 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/locate/csda .

    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.