IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v90y2003i2p435-444.html
   My bibliography  Save this article

Closed-form likelihoods for Arnason--Schwarz models

Author

Listed:
  • R. King

Abstract

We provide a general framework for the computationally efficient analysis, both Bayesian and classical, of integrated multi-site recovery/recapture models in the presence of individual-level covariates by extending the basic Arnason--Schwarz models and deriving closed-form likelihood expressions, together with corresponding sufficient statistics. Copyright Biometrika Trust 2003, Oxford University Press.

Suggested Citation

  • R. King, 2003. "Closed-form likelihoods for Arnason--Schwarz models," Biometrika, Biometrika Trust, vol. 90(2), pages 435-444, June.
    • Handle: RePEc:oup:biomet:v:90:y:2003:i:2:p:435-444
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. McCrea, R.S., 2012. "Sufficient statistic likelihood construction for age- and time-dependent multi-state joint recapture and recovery data," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 357-359.
    2. S. A. Sisson & Y. Fan, 2009. "Towards automating model selection for a mark–recapture–recovery analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(2), pages 247-266, May.
    3. Blanca Sarzo & Ruth King & David Conesa & Jonas Hentati-Sundberg, 2021. "Correcting Bias in Survival Probabilities for Partially Monitored Populations via Integrated Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(2), pages 200-219, June.
    4. Diana J. Cole, 2019. "Parameter redundancy and identifiability in hidden Markov models," METRON, Springer;Sapienza Università di Roma, vol. 77(2), pages 105-118, August.
    5. Rachel S. McCrea & Byron J. T. Morgan, 2011. "Multistate Mark–Recapture Model Selection Using Score Tests," Biometrics, The International Biometric Society, vol. 67(1), pages 234-241, March.
    6. Hannah Worthington & Rachel S. McCrea & Ruth King & Richard A. Griffiths, 2019. "Estimation of Population Size When Capture Probability Depends on Individual States," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(1), pages 154-172, March.

    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:oup:biomet:v:90:y:2003:i:2:p:435-444. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/biomet .

    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.