抄録
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.
本文言語 | English |
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ページ(範囲) | 644-655 |
ページ数 | 12 |
ジャーナル | Biometrics |
巻 | 66 |
号 | 2 |
DOI | |
出版ステータス | Published - 2010 6 1 |
ASJC Scopus subject areas
- Statistics and Probability
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Agricultural and Biological Sciences(all)
- Applied Mathematics