We propose a method for estimating the size of a population in a multiple record system in the presence of missing data. The method is based on a latent class model where the parameters and the latent structure are estimated using a Gibbs sampler. The proposed approach is illustrated through the analysis of a data set already known in the literature, which consists of five registrations of neural tube defects.

中文翻译：

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存在缺失数据时用于捕获-重新捕获的贝叶斯潜在类模型

我们提出了一种在存在缺失数据的情况下估计多记录系统中人口规模的方法。该方法基于潜在类模型，其中使用 Gibbs 采样器估计参数和潜在结构。通过分析文献中已知的数据集来说明所提出的方法，该数据集由五个神经管缺陷登记组成。