"The paper presents probability models to recover information on migration flows from incomplete data. Models are used to predict migration and to combine data from different sources.... Two models are considered: the binomial (multinomial) model, which underlies the logit model and the logistic regression, and the Poisson model, which underlies the loglinear model, the log-rate model and the Poisson regression.... By way of illustration, the probabilistic approach and the EM algorithm are applied to two different missing data problems." (EXCERPT)

中文翻译：

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迁移流间接估计的建模方法：从熵到 EM

“本文提出了概率模型，以从不完整的数据中恢复有关迁移流的信息。模型用于预测迁移并组合来自不同来源的数据......考虑了两种模型：二项式（多项式）模型，它是 logit 模型的基础和逻辑回归，以及作为对数线性模型、对数率模型和泊松回归的基础的泊松模型……举例来说，概率方法和 EM 算法应用于两个不同的缺失数据问题。 ” （摘抄）