Background: The Rogers–Castro model migration schedule is a key model for migration trends over the life course. It is applied in a wide variety of settings by demographers to examine the relationship between age and migration intensity. This model is nonlinear and can have up to 13 parameters, which can make estimation difficult. Existing techniques for parameter estimation can lead to issues such as nonconvergence, sensitivity to initial values, or optimization algorithms that do not reach the global optimum. Objective: We propose a new method of estimating Rogers–Castro model migration schedule parameters that overcomes most common difficulties. Methods: We apply a Bayesian framework for fitting the Rogers–Castro model. We also provide the R package rcbayes with functions to easily apply our proposed methodology. Results: We illustrate how this model and the R package can be used in a variety of settings by applying the model to data from the American Community Survey. Contribution: We provide a novel and easy-to-use approach for estimating Rogers–Castro model parameters. Our approach is formalized in an R package that makes parameter estimation and Bayesian methods more accessible for demographers and other researchers.

中文翻译：

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Rogers-Castro 模型迁移计划的贝叶斯实现：参数估计的替代技术（作者：Jessie Yeung、Monica Alexander、Tim Riffe）


背景：罗杰斯-卡斯特罗模型移民时间表是生命历程中移民趋势的关键模型。人口统计学家将其应用于各种环境中，以研究年龄与迁移强度之间的关系。该模型是非线性的，最多可以有 13 个参数，这使得估计变得困难。现有的参数估计技术可能会导致不收敛、对初始值敏感或优化算法无法达到全局最优等问题。目标：我们提出了一种估计 Rogers-Castro 模型迁移时间表参数的新方法，克服了最常见的困难。方法：我们应用贝叶斯框架来拟合罗杰斯-卡斯特罗模型。我们还提供 R 包 rcbayes 和函数来轻松应用我们提出的方法。结果：我们通过将该模型应用于美国社区调查的数据来说明如何在各种设置中使用该模型和 R 包。贡献：我们提供了一种新颖且易于使用的方法来估计 Rogers-Castro 模型参数。我们的方法在 R 包中形式化，使人口统计学家和其他研究人员更容易使用参数估计和贝叶斯方法。