IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v63y2007i1p252-258.html
   My bibliography  Save this article

An Estimating Function Approach to Inference for Inhomogeneous Neyman–Scott Processes

Author

Listed:
  • Rasmus Plenge Waagepetersen

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:biomet:v:63:y:2007:i:1:p:252-258
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2006.00667.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. D. Stoyan, 1992. "Statistical estimation of model parameters of planar neyman-scott cluster processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 39(1), pages 67-74, December.
    2. 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.
    3. 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.
    4. Baddeley, Adrian & Turner, Rolf, 2005. "spatstat: An R Package for Analyzing Spatial Point Patterns," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i06).
    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. 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).
    2. Michaela Prokešová & Jiří Dvořák & Eva B. Vedel Jensen, 2017. "Two-step estimation procedures for inhomogeneous shot-noise Cox processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(3), pages 513-542, June.
    3. Nicoletta D’Angelo & Marianna Siino & Antonino D’Alessandro & Giada Adelfio, 2022. "Local spatial log-Gaussian Cox processes for seismic data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(4), pages 633-671, December.
    4. Eric Marcon & Florence Puech, 2012. "A typology of distance-based measures of spatial concentration," Working Papers halshs-00679993, HAL.
    5. Marcon, Eric & Puech, Florence, 2017. "A typology of distance-based measures of spatial concentration," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 56-67.
    6. Amanda S. Hering & Sean Bair, 2014. "Characterizing spatial and chronological target selection of serial offenders," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(1), pages 123-140, January.
    7. Tilman M. Davies & Martin L. Hazelton, 2013. "Assessing minimum contrast parameter estimation for spatial and spatiotemporal log‐Gaussian Cox processes," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(4), pages 355-389, November.
    8. Marcon, Eric & Traissac, Stéphane & Puech, Florence & Lang, Gabriel, 2015. "Tools to Characterize Point Patterns: dbmss for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(c03).
    9. Laura Anton-Sanchez & Pedro Larrañaga & Ruth Benavides-Piccione & Isabel Fernaud-Espinosa & Javier DeFelipe & Concha Bielza, 2017. "Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-14, June.
    10. Angelo Mazza & Antonio Punzo, 2016. "Spatial attraction in migrants' settlement patterns in the city of Catania," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 35(5), pages 117-138.
    11. 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.
    12. Marj Tonini & Andrea Pedrazzini & Ivanna Penna & Michel Jaboyedoff, 2014. "Spatial pattern of landslides in Swiss Rhone Valley," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(1), pages 97-110, August.
    13. Jean-François Coeurjolly & Jesper Møller & Rasmus Waagepetersen, 2017. "A Tutorial on Palm Distributions for Spatial Point Processes," International Statistical Review, International Statistical Institute, vol. 85(3), pages 404-420, December.
    14. 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.
    15. 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.
    16. 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.
    17. Yehua Li & Yongtao Guan, 2014. "Functional Principal Component Analysis of Spatiotemporal Point Processes With Applications in Disease Surveillance," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1205-1215, September.
    18. Ian W. Renner & David I. Warton, 2013. "Equivalence of MAXENT and Poisson Point Process Models for Species Distribution Modeling in Ecology," Biometrics, The International Biometric Society, vol. 69(1), pages 274-281, March.
    19. Jesper Møller & Carlos Díaz‐Avalos, 2010. "Structured Spatio‐Temporal Shot‐Noise Cox Point Process Models, with a View to Modelling Forest Fires," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(1), pages 2-25, March.
    20. Gabriel Lang & Eric Marcon & Florence Puech, 2020. "Distance-based measures of spatial concentration: introducing a relative density function," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 243-265, April.

    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:bla:biomet:v:63:y:2007:i:1:p:252-258. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.