Forming post-strata via Bayesian treed capture-recapture models

• 成果类型: Article
• 署名作者: Wang, Xinlei; Lim, Johan; Stokes, S. Lynne
• 署名单位: Southern Methodist University; Yonsei University; Southern Methodist University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/93.4.861
• 发表日期: 2006
• 页码: 861876
• 关键词: auxiliary variables; monte-carlo; Heterogeneity; population; size

摘要

For the problem of dual system estimation, we propose a Bayesian treed capture-recapture model to account for heterogeneity of capture probabilities where individual auxiliary information is available. The model uses a binary tree to partition the covariate space into 'homogeneous' regions, within each of which the capture response can be described adequately by a simple model that assumes equal catchability. The attractive features of the proposed model include reduction of correlation bias, robustness and practical flexibility as well as simplicity and interpretability. In addition, it provides a systematic and effective way of forming post-strata for the Sekar-Deming estimator of population size. We compare the performance of estimators based on this model to those of alternative estimators in three scenarios.