Capture-recapture estimation using finite mixtures of arbitrary dimension

Biometrics. 2010 Jun;66(2):644-55. doi: 10.1111/j.1541-0420.2009.01289.x. Epub 2009 Jun 12.


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.

MeSH terms

  • Animals
  • Biometry / methods*
  • Ecology / statistics & numerical data
  • Markov Chains*
  • Monte Carlo Method*
  • Probability
  • Rabbits