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Latent class recapture models with flexible behavioural response

Author

Listed:
  • Alessio Farcomeni

    (Università di Roma "La Sapienza", Italy)

Abstract

We propose a class of models for population size estimation in capture-recapture studies, allowing for flexible behavioural and time response, observed heterogeneity and unobserved heterogeneity. The latter is taken into account by means of discrete random variables. The conditional likelihood is maximized through an efficient EM based on the Aitchinson-Silvey algorithm.

Suggested Citation

  • Alessio Farcomeni, 2015. "Latent class recapture models with flexible behavioural response," Statistica, Department of Statistics, University of Bologna, vol. 75(1), pages 5-17.
    • Handle: RePEc:bot:rivsta:v:75:y:2015:i:1:p:5-17
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    References listed on IDEAS

    as
    1. J. Andrew Royle, 2009. "Analysis of Capture–Recapture Models with Individual Covariates Using Data Augmentation," Biometrics, The International Biometric Society, vol. 65(1), pages 267-274, March.
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    4. Bartolucci, Francesco & Forcina, Antonio, 2006. "A Class of Latent Marginal Models for CaptureRecapture Data With Continuous Covariates," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 786-794, June.
    5. Alessio Farcomeni & Luca Tardella, 2010. "Reference Bayesian methods for recapture models with heterogeneity," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(1), pages 187-208, May.
    6. D. Oakes, 1999. "Direct calculation of the information matrix via the EM," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 479-482, April.
    7. A. Farcomeni, 2016. "A general class of recapture models based on the conditional capture probabilities," Biometrics, The International Biometric Society, vol. 72(1), pages 116-124, March.
    8. Fred L. Ramsey & Dale Usner, 2003. "Persistence and Heterogeneity in Habitat Selection Studies Using Radio Telemetry," Biometrics, The International Biometric Society, vol. 59(2), pages 332-340, June.
    9. R. M. Fewster & P. E. Jupp, 2009. "Inference on population size in binomial detectability models," Biometrika, Biometrika Trust, vol. 96(4), pages 805-820.
    10. 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.
    11. F. Bartolucci & A. Farcomeni & F. Pennoni, 2014. "Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 433-465, September.
    12. A. Farcomeni, 2011. "Recapture models under equality constraints for the conditional capture probabilities," Biometrika, Biometrika Trust, vol. 98(1), pages 237-242.
    13. 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.
    14. Hajo Holzmann & Axel Munk & Walter Zucchini, 2006. "On Identifiability in Capture–Recapture Models," Biometrics, The International Biometric Society, vol. 62(3), pages 934-936, September.
    15. Evans, R.J. & Forcina, A., 2013. "Two algorithms for fitting constrained marginal models," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 1-7.
    16. Danilo Fegatelli & Luca Tardella, 2013. "Improved inference on capture recapture models with behavioural effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(1), pages 45-66, March.
    17. Chang Xuan Mao, 2008. "On the Nonidentifiability of Population Sizes," Biometrics, The International Biometric Society, vol. 64(3), pages 977-979, September.
    18. 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.
    19. Shirley Pledger, 2005. "The Performance of Mixture Models in Heterogeneous Closed Population Capture–Recapture," Biometrics, The International Biometric Society, vol. 61(3), pages 868-873, September.
    20. Hsin-Chou Yang & Anne Chao, 2005. "Modeling Animals' Behavioral Response by Markov Chain Models for Capture–Recapture Experiments," Biometrics, The International Biometric Society, vol. 61(4), pages 1010-1017, December.
    21. Bartolucci, Francesco & Farcomeni, Alessio, 2009. "A Multivariate Extension of the Dynamic Logit Model for Longitudinal Data Based on a Latent Markov Heterogeneity Structure," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 816-831.
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