Abstract:
:Reversible jump Markov chain Monte Carlo (RJMCMC) methods are used to fit Bayesian capture-recapture models incorporating heterogeneity in individuals and samples. Heterogeneity in capture probabilities comes from finite mixtures and/or fixed sample effects allowing for interactions. Estimation by RJMCMC allows automatic model selection and/or model averaging. Priors on the parameters stabilize the estimates and produce realistic credible intervals for population size for overparameterized models, in contrast to likelihood-based methods. To demonstrate the approach we analyze the standard Snowshoe hare and Cottontail rabbit data sets from ecology, a reliability testing data set.
journal_name
Biometricsjournal_title
Biometricsauthors
Arnold R,Hayakawa Y,Yip Pdoi
10.1111/j.1541-0420.2009.01289.xsubject
Has Abstractpub_date
2010-06-01 00:00:00pages
644-55issue
2eissn
0006-341Xissn
1541-0420pii
BIOM1289journal_volume
66pub_type
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