Capture-recapture estimation using finite mixtures of arbitrary dimension.

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

Biometrics

journal_title

Biometrics

authors

Arnold R,Hayakawa Y,Yip P

doi

10.1111/j.1541-0420.2009.01289.x

subject

Has Abstract

pub_date

2010-06-01 00:00:00

pages

644-55

issue

2

eissn

0006-341X

issn

1541-0420

pii

BIOM1289

journal_volume

66

pub_type

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