IDEAS home Printed from https://ideas.repec.org/a/mtn/ancoec/2002301.html
   My bibliography  Save this article

Resampling estimators of specie richness from presence-absence data: why they don't work

Author

Listed:
  • Luana D'Alessandro
  • Lorenzo Fattorini

Abstract

No abstract is available for this item.

Suggested Citation

  • Luana D'Alessandro & Lorenzo Fattorini, 2002. "Resampling estimators of specie richness from presence-absence data: why they don't work," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 3-17.
    • Handle: RePEc:mtn:ancoec:2002:3:01
    as

    Download full text from publisher

    File URL: https://www.dss.uniroma1.it/RePec/mtn/articoli/2002-LX-3_4-1.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sueli Mingoti, 1999. "Bayesian estimator for the total number of distinct species when quadrat sampling is used," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(4), pages 469-483.
    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. Alessandro Chiarucci & Rosa Maria Di Biase & Lorenzo Fattorini & Marzia Marcheselli & Caterina Pisani, 2017. "Joining the Incompatible: Exploiting Floristic Lists for the Sample-based Estimation of Species Richness," Department of Economics University of Siena 753, Department of Economics, University of Siena.

    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. Chang Dorea & Sueli Mingoti, 2006. "Estimating the total number of distinct species using quadrat sampling and under-dependence structure," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(5), pages 497-512.
    2. Sueli Mingoti, 2000. "A stepwise Bayesian estimator for the total number of distinct species in finite populations: Sampling by elements," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(5), pages 651-670.
    3. Peter J. Haas & Yushan Liu & Lynne Stokes, 2006. "An Estimator of Number of Species from Quadrat Sampling," Biometrics, The International Biometric Society, vol. 62(1), pages 135-141, March.
    4. Jérôme A. Dupuis & Jean Joachim, 2006. "Bayesian Estimation of Species Richness from Quadrat Sampling Data in the Presence of Prior Information," Biometrics, The International Biometric Society, vol. 62(3), pages 706-712, September.

    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:mtn:ancoec:2002:3:01. 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: Marco Alfo' (email available below). General contact details of provider: .

    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.