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A General Class of Recapture Models Based on the Conditional Capture Probabilities

机译:基于条件捕获概率的通用捕获模型

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摘要

We propose an Mhotb model for population size estimation in capture-recapture studies. The tb part is based on equality constraints for the conditional capture probabilities, leading to an extremely rich model class. Observed and unobserved heterogeneity are dealt with by means of a logistic parameterization. In order to explore the model class, we introduce a penalized version of the likelihood. The conditional likelihood and penalized conditional likelihood are maximized by means of efficient EM algorithms. Simulations and two real data examples illustrate the approach.
机译:我们提出了一个Mhotb模型,用于捕获-捕获研究中的人口规模估计。 tb部分基于条件捕获概率的相等性约束,从而导致模型类非常丰富。观察到的和未观察到的异质性通过逻辑参数化处理。为了探讨模型类别,我们介绍了可能性的一种惩罚形式。通过高效的EM算法,可以使条件似然和惩罚性条件似然最大化。仿真和两个实际数据示例说明了该方法。

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