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This article presents a Bayesian analysis of mark-recapture-recovery data on Soay sheep. A reversible jump Markov chain Monte Carlo technique is used to determine age classes of common survival, and to model the survival probabilities in those classes using logistic regression. This involves environmental and individual covariates, as well as random effects. Auxiliary variables are used to impute missing covariates measured on individual sheep. The Bayesian approach suggests different models from those previously obtained using classical statistical methods. Following model averaging, features that were not previously detected, and which are of ecological importance, are identified.

Original publication

DOI

10.1111/j.1541-0420.2005.00404.x

Type

Journal article

Journal

Biometrics

Publication Date

03/2006

Volume

62

Pages

211 - 220

Keywords

Animals, Bayes Theorem, Ecology, Logistic Models, Markov Chains, Monte Carlo Method, Sheep, Survival Rate