A Review of the Use of Conditional Likelihood in Capture‐Recapture Experiments
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DOI: j.1751-5823.2011.00157.x
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Cited by:
- 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.
- Matthew R. Schofield & Richard J. Barker & William A. Link & Heloise Pavanato, 2023. "Estimating population size: The importance of model and estimator choice," Biometrics, The International Biometric Society, vol. 79(4), pages 3803-3817, December.
- John Ashton & Tim Burnett & Ivan Diaz Rainey & Peter L. Ormosi, 2018. "Has the financial regulatory environment improved in the UK? Capture-Recapture approach to estimate detection and deterrence," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2018-03, Centre for Competition Policy, University of East Anglia, Norwich, UK..
- 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.
- 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.
- 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.
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