TY - JOUR
AU - Yip, Paul
AB - Summary 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.
TI - Capture–Recapture Estimation Using Finite Mixtures of Arbitrary Dimension
JF - Biometrics
DO - 10.1111/j.1541-0420.2009.01289.x
DA - 2010-06-01
UR - https://www.deepdyve.com/lp/oxford-university-press/capture-recapture-estimation-using-finite-mixtures-of-arbitrary-r4C3V2YIWE
SP - 644
VL - 66
IS - 2
DP - DeepDyve
ER -