IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v29y2002i1-4p315-327.html
   My bibliography  Save this article

Modelling heterogeneity of survival in band-recovery data using mixtures

Author

Listed:
  • Shirley Pledger
  • Carl Schwarz

Abstract

Finite mixture methods are applied to bird band-recovery studies to allow for heterogeneity of survival. Birds are assumed to belong to one of finitely many groups, each of which has its own survival rate (or set of survival rates varying by time and/or age). The group to which a specific animal belongs is not known, so its survival probability is a random variable from a finite mixture. Heterogeneity is thus modelled as a latent effect. This gives a wide selection of likelihood-based models, which may be compared using likelihood ratio tests. These models are discussed with reference to real and simulated data, and compared with previous models.

Suggested Citation

  • Shirley Pledger & Carl Schwarz, 2002. "Modelling heterogeneity of survival in band-recovery data using mixtures," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(1-4), pages 315-327.
  • Handle: RePEc:taf:japsta:v:29:y:2002:i:1-4:p:315-327
    DOI: 10.1080/02664760120108737
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/02664760120108737
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02664760120108737?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. Shirley Pledger, 2000. "Unified Maximum Likelihood Estimates for Closed Capture–Recapture Models Using Mixtures," Biometrics, The International Biometric Society, vol. 56(2), pages 434-442, June.
    2. Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
    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. Shirley Pledger & Kenneth H. Pollock & James L. Norris, 2003. "Open Capture-Recapture Models with Heterogeneity: I. Cormack-Jolly-Seber Model," Biometrics, The International Biometric Society, vol. 59(4), pages 786-794, December.
    2. Ann E. McKellar & Roland Langrock & Jeffrey R. Walters & Dylan C. Kesler, 2015. "Using mixed hidden Markov models to examine behavioral states in a cooperatively breeding bird," Behavioral Ecology, International Society for Behavioral Ecology, vol. 26(1), pages 148-157.
    3. B. J. T. Morgan & M. S. Ridout, 2008. "A new mixture model for capture heterogeneity," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(4), pages 433-446, September.

    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. Henry, Olan T. & Olekalns, Nilss & Suardi, Sandy, 2007. "Testing for rate dependence and asymmetry in inflation uncertainty: Evidence from the G7 economies," Economics Letters, Elsevier, vol. 94(3), pages 383-388, March.
    2. Garcia, Rene, 1998. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 763-788, August.
    3. Vasudeva N. R. Murthy & Emmanuel Anoruo, 2009. "Are Per Capita Real GDP Series in African Countries Non-stationary or Non-linear? What does Empirical Evidence Reveal?," Economics Bulletin, AccessEcon, vol. 29(4), pages 2492-2504.
    4. Paul S. F. Yip & Hua-Zhen Lin & Liqun Xi, 2005. "A Semiparametric Method for Estimating Population Size for Capture–Recapture Experiments with Random Covariates in Continuous Time," Biometrics, The International Biometric Society, vol. 61(4), pages 1085-1092, December.
    5. Fabra, Natalia & Toro, Juan, 2005. "Price wars and collusion in the Spanish electricity market," International Journal of Industrial Organization, Elsevier, vol. 23(3-4), pages 155-181, April.
    6. Olan T. Henry & Nilss Olekalns & Kalvinder Shields, 2002. "Non-linear Co-Movements in Output Growth: Evidence from the United States and Australia," Department of Economics - Working Papers Series 857, The University of Melbourne.
    7. Christoph Rothe & Philipp Sibbertsen, 2006. "Phillips-Perron-type unit root tests in the nonlinear ESTAR framework," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(3), pages 439-456, September.
    8. Chang Xuan Mao & Na You, 2009. "On Comparison of Mixture Models for Closed Population Capture–Recapture Studies," Biometrics, The International Biometric Society, vol. 65(2), pages 547-553, June.
    9. Gabriel Vasco J. & Alexandre Fernando & Bação Pedro, 2008. "The Consumption-Wealth Ratio under Asymmetric Adjustment," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(4), pages 1-32, December.
    10. Andrea Beltratti & Claudio Morana, 2006. "Net Inflows and Time-Varying Alphas: The Case of Hedge Funds," ICER Working Papers 30-2006, ICER - International Centre for Economic Research.
    11. Clarida, Richard H. & Sarno, Lucio & Taylor, Mark P. & Valente, Giorgio, 2003. "The out-of-sample success of term structure models as exchange rate predictors: a step beyond," Journal of International Economics, Elsevier, vol. 60(1), pages 61-83, May.
    12. Chen, Shan & Insley, Margaret, 2012. "Regime switching in stochastic models of commodity prices: An application to an optimal tree harvesting problem," Journal of Economic Dynamics and Control, Elsevier, vol. 36(2), pages 201-219.
    13. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    14. Scheiblecker, Marcus, 2013. "Between cointegration and multicointegration: Modelling time series dynamics by cumulative error correction models," Economic Modelling, Elsevier, vol. 31(C), pages 511-517.
    15. Marcus Scheiblecker, 2017. "Modelling Short-run Money Demand for the US," Applied Economics and Finance, Redfame publishing, vol. 4(5), pages 9-20, September.
    16. Peter Tillmann, 2003. "The Regime‐Dependent Determination of Credibility: A New Look at European Interest Rate Differentials," German Economic Review, Verein für Socialpolitik, vol. 4(4), pages 409-431, November.
    17. Ahoniemi, Katja & Lanne, Markku, 2009. "Joint modeling of call and put implied volatility," International Journal of Forecasting, Elsevier, vol. 25(2), pages 239-258.
    18. Markku Lanne, 2006. "Nonlinear dynamics of interest rate and inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1157-1168, December.
    19. Mario Cerrato & Christian De Peretti & Nick Sarantis, 2007. "A nonlinear panel unit root test under cross section dependence," Documents de recherche 07-12, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    20. Ben C. Stevenson & Rachel M. Fewster & Koustubh Sharma, 2022. "Spatial correlation structures for detections of individuals in spatial capture–recapture models," Biometrics, The International Biometric Society, vol. 78(3), pages 963-973, 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:taf:japsta:v:29:y:2002:i:1-4:p:315-327. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.