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Abundance estimation based on optimal estimating function with missing covariates in capture–recapture studies

Author

Listed:
  • Liu, Yang
  • Zhang, Xiuzhen
  • Li, Mengke
  • Liu, Guanfu
  • Zhu, Lin

Abstract

For the abundance parameter in capture–recapture studies with missing covariates, we propose an optimal-estimating-function-based estimator and develop a bootstrap procedure to construct the confidence interval. We illustrate our methods through simulations and the yellow-bellied prinia data.

Suggested Citation

  • Liu, Yang & Zhang, Xiuzhen & Li, Mengke & Liu, Guanfu & Zhu, Lin, 2019. "Abundance estimation based on optimal estimating function with missing covariates in capture–recapture studies," Statistics & Probability Letters, Elsevier, vol. 152(C), pages 15-20.
    • Handle: RePEc:eee:stapro:v:152:y:2019:i:c:p:15-20
    DOI: 10.1016/j.spl.2019.04.003
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    References listed on IDEAS

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    1. Richard Huggins & Wen‐Han Hwang, 2011. "A Review of the Use of Conditional Likelihood in Capture‐Recapture Experiments," International Statistical Review, International Statistical Institute, vol. 79(3), pages 385-400, December.
    2. Shen‐Ming Lee & Wen‐Han Hwang & Jean de Dieu Tapsoba, 2016. "Estimation in closed capture–recapture models when covariates are missing at random," Biometrics, The International Biometric Society, vol. 72(4), pages 1294-1304, December.
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