Continuous Covariates in Mark-Recapture-Recovery Analysis: A Comparison of Methods
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Publication:3076063
DOI10.1111/j.1541-0420.2010.01390.xzbMath1208.62167OpenAlexW1989911828WikidataQ46776067 ScholiaQ46776067MaRDI QIDQ3076063
Simon J. Bonner, Ruth King, Byron J. T. Morgan
Publication date: 17 February 2011
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/j.1541-0420.2010.01390.x
Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15)
Related Items (8)
Heterogeneous Capture-Recapture Models with Covariates: A Partial Likelihood Approach for Closed Populations ⋮ Maximum likelihood estimation of mark-recapture-recovery models in the presence of continuous covariates ⋮ Analysing mark-recapture-recovery data in the presence of missing covariate data via multiple imputation ⋮ A Bayesian approach to fitting Gibbs processes with temporal random effects ⋮ Full open population capture-recapture models with individual covariates ⋮ Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models ⋮ Correcting bias in survival probabilities for partially monitored populations via integrated models ⋮ Laplace approximations for capture-recapture models in the presence of individual heterogeneity
Uses Software
Cites Work
- Posterior predictive \(p\)-values
- A New Method for Analysing Discrete Life History Data with Missing Covariate Values
- Analyzing Complex Capture–Recapture Data in the Presence of Individual and Temporal Covariates and Model Uncertainty
- The use of auxiliary variables in capture-recapture modelling: An overview
- An Extension of the Cormack–Jolly–Seber Model for Continuous Covariates with Application to Microtus pennsylvanicus
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