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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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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. 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).
    3. 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.

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