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Heterogeneous Capture–Recapture Models with Covariates: A Partial Likelihood Approach for Closed Populations

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  • Jakub Stoklosa
  • Wen-Han Hwang
  • Sheng-Hai Wu
  • Richard Huggins

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  • Jakub Stoklosa & Wen-Han Hwang & Sheng-Hai Wu & Richard Huggins, 2011. "Heterogeneous Capture–Recapture Models with Covariates: A Partial Likelihood Approach for Closed Populations," Biometrics, The International Biometric Society, vol. 67(4), pages 1659-1665, December.
    • Handle: RePEc:bla:biomet:v:67:y:2011:i:4:p:1659-1665
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2011.01596.x
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    References listed on IDEAS

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    1. Robert M. Dorazio & J. Andrew Royle, 2003. "Mixture Models for Estimating the Size of a Closed Population When Capture Rates Vary among Individuals," Biometrics, The International Biometric Society, vol. 59(2), pages 351-364, June.
    2. Simon J. Bonner & Byron J. T. Morgan & Ruth King, 2010. "Continuous Covariates in Mark-Recapture-Recovery Analysis: A Comparison of Methods," Biometrics, The International Biometric Society, vol. 66(4), pages 1256-1265, December.
    3. William A. Link, 2003. "Nonidentifiability of Population Size from Capture-Recapture Data with Heterogeneous Detection Probabilities," Biometrics, The International Biometric Society, vol. 59(4), pages 1123-1130, December.
    4. Kenneth Pollock, 2002. "The use of auxiliary variables in capture-recapture modelling: An overview," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(1-4), pages 85-102.
    5. 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.
    6. Richard Huggins & Wen‐Han Hwang, 2007. "Non‐parametric estimation of population size from capture–recapture data when the capture probability depends on a covariate," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(4), pages 429-443, August.
    7. Wen-Han Hwang & Steve Y. H. Huang, 2003. "Estimation in Capture-Recapture Models When Covariates Are Subject to Measurement Errors," Biometrics, The International Biometric Society, vol. 59(4), pages 1113-1122, December.
    8. E. A. Catchpole & B. J. T. Morgan & G. Tavecchia, 2008. "A new method for analysing discrete life history data with missing covariate values," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(2), pages 445-460, April.
    9. Brent A. Coull & Alan Agresti, 1999. "The Use of Mixed Logit Models to Reflect Heterogeneity in Capture-Recapture Studies," Biometrics, The International Biometric Society, vol. 55(1), pages 294-301, March.
    10. S. J. Bonner & C. J. Schwarz, 2006. "An Extension of the Cormack–Jolly–Seber Model for Continuous Covariates with Application to Microtus pennsylvanicus," Biometrics, The International Biometric Society, vol. 62(1), pages 142-149, March.
    11. 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.
    12. Xuan Mao, Chang, 2007. "Estimating population sizes for capture-recapture sampling with binomial mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5211-5219, July.
    13. Kani Chen, 2001. "Parametric and semiparametric models for recapture and removal studies: a likelihood approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(3), pages 607-619.
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    Cited by:

    1. Stoklosa, Jakub & Huang, Yih-Huei & Furlan, Elise & Hwang, Wen-Han, 2016. "On quadratic logistic regression models when predictor variables are subject to measurement error," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 109-121.
    2. Riki Herliansyah & Ruth King & Stuart King, 2022. "Laplace Approximations for Capture–Recapture Models in the Presence of Individual Heterogeneity," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(3), pages 401-418, September.
    3. Yang Liu & Yukun Liu & Yan Fan & Han Geng, 2018. "Likelihood ratio confidence interval for the abundance under binomial detectability models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(5), pages 549-568, July.
    4. Yang Liu & Yukun Liu & Pengfei Li & Lin Zhu, 2021. "Maximum likelihood abundance estimation from capture‐recapture data when covariates are missing at random," Biometrics, The International Biometric Society, vol. 77(3), pages 1050-1060, September.
    5. Wen-Han Hwang & Jakub Stoklosa & Ching-Yun Wang, 2022. "Population Size Estimation Using Zero-Truncated Poisson Regression with Measurement Error," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 303-320, June.
    6. Yee, Thomas W. & Stoklosa, Jakub & Huggins, Richard M., 2015. "The VGAM Package for Capture-Recapture Data Using the Conditional Likelihood," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(i05).

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