IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v69y2013i3p766-775.html
   My bibliography  Save this article

Mark-Recapture with Multiple, Non-Invasive Marks

Author

Listed:
  • Simon J Bonner
  • Jason Holmberg

Abstract

No abstract is available for this item.

Suggested Citation

  • Simon J Bonner & Jason Holmberg, 2013. "Mark-Recapture with Multiple, Non-Invasive Marks," Biometrics, The International Biometric Society, vol. 69(3), pages 766-775, September.
    • Handle: RePEc:bla:biomet:v:69:y:2013:i:3:p:766-775
    DOI: 10.1111/biom.12045
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/biom.12045
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1111/biom.12045?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. William A. Link & Richard J. Barker, 2005. "Modeling Association among Demographic Parameters in Analysis of Open Population Capture–Recapture Data," Biometrics, The International Biometric Society, vol. 61(1), pages 46-54, March.
    2. Janine A. Wright & Richard J. Barker & Matthew R. Schofield & Alain C. Frantz & Andrea E. Byrom & Dianne M. Gleeson, 2009. "Incorporating Genotype Uncertainty into Mark–Recapture-Type Models For Estimating Abundance Using DNA Samples," Biometrics, The International Biometric Society, vol. 65(3), pages 833-840, September.
    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. R. T. R. Vale & R. M. Fewster & E. L. Carroll & N. J. Patenaude, 2014. "Maximum likelihood estimation for model M t,α for capture–recapture data with misidentification," Biometrics, The International Biometric Society, vol. 70(4), pages 962-971, December.

    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. Richard J. Barker & Matthew R. Schofield & Janine A. Wright & Alain C. Frantz & Chris Stevens, 2014. "Closed-population capture–recapture modeling of samples drawn one at a time," Biometrics, The International Biometric Society, vol. 70(4), pages 775-782, December.
    2. Robert M. Dorazio, 2020. "Objective prior distributions for Jolly‐Seber models of zero‐augmented data," Biometrics, The International Biometric Society, vol. 76(4), pages 1285-1296, December.
    3. R. M. Fewster, 2017. "Some applications of genetics in statistical ecology," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(4), pages 349-379, October.
    4. Laura Cowen & Carl J. Schwarz, 2006. "The Jolly–Seber Model with Tag Loss," Biometrics, The International Biometric Society, vol. 62(3), pages 699-705, September.
    5. Manuel Wiesenfarth & Carlos Matías Hisgen & Thomas Kneib & Carmen Cadarso-Suarez, 2014. "Bayesian Nonparametric Instrumental Variables Regression Based on Penalized Splines and Dirichlet Process Mixtures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 468-482, July.
    6. Macbeth, Gilbert M. & Broderick, Damien & Ovenden, Jennifer R. & Buckworth, Rik C., 2011. "Likelihood-based genetic mark–recapture estimates when genotype samples are incomplete and contain typing errors," Theoretical Population Biology, Elsevier, vol. 80(3), pages 185-196.
    7. Qian, Guoqi & Li, Ning & Huggins, Richard, 2011. "Using capture-recapture data and hybrid Monte Carlo sampling to estimate an animal population affected by an environmental catastrophe," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 655-666, January.
    8. Murray G. Efford & Matthew R. Schofield, 2020. "A spatial open‐population capture‐recapture model," Biometrics, The International Biometric Society, vol. 76(2), pages 392-402, June.
    9. Richard Huggins & Jakub Stoklosa & Cameron Roach & Paul Yip, 2018. "Estimating the size of an open population using sparse capture–recapture data," Biometrics, The International Biometric Society, vol. 74(1), pages 280-288, March.
    10. R. B. O'Hara & S. Lampila & M. Orell, 2009. "Estimation of Rates of Births, Deaths, and Immigration from Mark–Recapture Data," Biometrics, The International Biometric Society, vol. 65(1), pages 275-281, March.
    11. Xinyi Lu & Mevin B. Hooten & Andee Kaplan & Jamie N. Womble & Michael R. Bower, 2022. "Improving Wildlife Population Inference Using Aerial Imagery and Entity Resolution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 364-381, June.
    12. Matthew R. Schofield & Richard J. Barker & Nicholas Gelling, 2018. "Continuous†time capture–recapture in closed populations," Biometrics, The International Biometric Society, vol. 74(2), pages 626-635, June.
    13. Ben C. Stevenson & David L. Borchers & Rachel M. Fewster, 2019. "Cluster capture‐recapture to account for identification uncertainty on aerial surveys of animal populations," Biometrics, The International Biometric Society, vol. 75(1), pages 326-336, March.
    14. Li‐Chun Zhang & Tiziana Tuoto, 2021. "Linkage‐data linear regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 522-547, April.
    15. Matthew R. Schofield & Richard J. Barker, 2020. "Rejoinder to “On continuous‐time capture‐recapture in closed populations”," Biometrics, The International Biometric Society, vol. 76(3), pages 1034-1035, September.
    16. R. T. R. Vale & R. M. Fewster & E. L. Carroll & N. J. Patenaude, 2014. "Maximum likelihood estimation for model M t,α for capture–recapture data with misidentification," Biometrics, The International Biometric Society, vol. 70(4), pages 962-971, December.
    17. Gimenez, Olivier & Lebreton, Jean-Dominique & Gaillard, Jean-Michel & Choquet, Rémi & Pradel, Roger, 2012. "Estimating demographic parameters using hidden process dynamic models," Theoretical Population Biology, Elsevier, vol. 82(4), pages 307-316.

    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:69:y:2013:i:3:p:766-775. 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.