The classical approach to statistical analysis is usually based upon finding values for model parameters that maximize the likelihood function. Model choice in this context is often also based on the likelihood function, but with the addition of a penalty term for the number of parameters....

We provide a general framework for the computationally efficient analysis, both Bayesian and classical, of integrated multi-site recovery/recapture models in the presence of individual-level covariates by extending the basic Arnason--Schwarz models and deriving closed-form likelihood...

Extending the work of Dupuis (1995), we motivate a range of biologically plausible models for multiple-site capture-recapture and show how the original Gibbs sampling algorithm of Dupuis can be extended to obtain posterior model probabilities using reversible jump Markov chain Monte Carlo. This...