On Comparison of Mixture Models for Closed Population Capture–Recapture Studies

DOI10.1111/j.1541-0420.2008.01065.xzbMath1167.62011OpenAlexW1968256112WikidataQ46085834 ScholiaQ46085834MaRDI QIDQ3637003

Na You, Chang Xuan Mao

Publication date: 30 June 2009

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2008.01065.x

zbMATH Keywords

boundary problemsintrinsic biasbias decomposition

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to environmental and related topics (62P12) Sampling theory, sample surveys (62D05)

Related Items (9)

Latent class recapture models with flexible behavioural response ⋮ A Review of the Use of Conditional Likelihood in Capture-Recapture Experiments ⋮ Estimating population sizes with the Rasch model ⋮ A regression estimator for mixed binomial capture-recapture data ⋮ Identifiability and inferential issues in capture-recapture experiments with heterogeneous detection probabilities ⋮ On the Chao and Zelterman estimators in a binomial mixture model ⋮ Ratio plot and ratio regression with applications to social and medical sciences ⋮ A flexible ratio regression approach for zero-truncated capture-recapture counts ⋮ Improved inference on capture recapture models with behavioural effects

Cites Work

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• Estimating population sizes by catch-effort methods
• Estimating population sizes for capture-recapture sampling with binomial mixtures
• Mixture Models for Estimating the Size of a Closed Population When Capture Rates Vary among Individuals
• Estimating Population Size for Sparse Data in Capture-Recapture Experiments
• Nonidentifiability of Population Size from Capture‐Recapture Data with Heterogeneous Detection Probabilities
• Estimating the Size of a Truncated Sample
• Estimation of the size of a closed population when capture probabilities vary among animals
• Nonparametric MLE under Two Closed Capture-Recapture Models with Heterogeneity
• Unified Maximum Likelihood Estimates for Closed Capture–Recapture Models Using Mixtures
• Estimating Population Size Via Sample Coverage for Closed Capture-Recapture Models

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