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A robust P-spline approach to closed population capture–recapture models with time dependence and heterogeneity

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  • Stoklosa, Jakub
  • Huggins, Richard M.

Abstract

We extend the conditional likelihood approach to the analysis of capture–recapture experiments for closed populations by nonparametrically modeling the relationship between capture probabilities and individual covariates using P-splines. The model allows nonparametric functions of multivariate continuous covariates as well as categorical covariates and time effects, greatly enhancing the techniques available to an analyst. To implement this approach in practice, we found it necessary to develop a robust modification of the Horvitz–Thompson estimator. The method is illustrated on several data sets and a small simulation study is conducted.

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  • Stoklosa, Jakub & Huggins, Richard M., 2012. "A robust P-spline approach to closed population capture–recapture models with time dependence and heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 408-417.
    • Handle: RePEc:eee:csdana:v:56:y:2012:i:2:p:408-417
    DOI: 10.1016/j.csda.2011.08.004
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    1. Rivest Louis-Paul, 2011. "A Lower Bound Model for Multiple Record Systems Estimation with Heterogeneous Catchability," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-21, May.
    2. Marx, Brian D. & Eilers, Paul H. C., 1998. "Direct generalized additive modeling with penalized likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 28(2), pages 193-209, August.
    3. 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.
    4. 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.
    5. 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.
    6. Yee, Thomas W., 2010. "The VGAM Package for Categorical Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i10).
    7. Zwane, E. N. & van der Heijden, P. G. M., 2004. "Semiparametric models for capture-recapture studies with covariates," Computational Statistics & Data Analysis, Elsevier, vol. 47(4), pages 729-743, November.
    8. Young‐Ju Kim & Chong Gu, 2004. "Smoothing spline Gaussian regression: more scalable computation via efficient approximation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(2), pages 337-356, May.
    9. Muggeo, Vito M.R. & Ferrara, Giancarlo, 2008. "Fitting generalized linear models with unspecified link function: A P-spline approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2529-2537, January.
    10. Cantoni E. & Ronchetti E., 2001. "Robust Inference for Generalized Linear Models," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1022-1030, September.
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    Cited by:

    1. 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).
    2. Li, Haoqi & Lin, Huazhen & Yip, Paul S.F. & Li, Yuan, 2019. "Estimating population size of heterogeneous populations with large data sets and a large number of parameters," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 34-44.
    3. Fodé Tounkara & Louis‐Paul Rivest, 2015. "Mixture regression models for closed population capture–recapture data," Biometrics, The International Biometric Society, vol. 71(3), pages 721-730, September.

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