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Bayesian small area demography

机译：贝叶斯小区人口统计

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摘要

Demographers are facing increasing pressure to disaggregate their estimates and forecasts by characteristics such as region, ethnicity, and income. Traditional demographic methods were designed for large samples, and perform poorly with disaggregated data. Methods based on formal Bayesian statistical models offer better performance. We illustrate with examples from a long-term project to develop Bayesian approaches to demographic estimation and forecasting. In our first example, we estimate mortality rates disaggregated by age and sex for a small population. In our second example, we simultaneously estimate and forecast obesity prevalence disaggregated by age. We conclude by addressing two traditional objections to the use of Bayesian methods in statistical agencies.
机译：人口统计学家面临着越来越大的压力，以通过区域，种族和收入等特征分解其估计和预测。传统的人口统计学方法是为大型样品设计的，并且随着分解数据而言。基于正式贝叶斯统计模型的方法提供了更好的性能。我们用长期项目的示例说明了发展贝叶斯估计和预测的贝叶斯途径。在我们的第一个例子中，我们估计死亡率对年龄和性别进行小小的人口分解。在我们的第二个例子中，我们同时估计和预测年龄分列的肥胖普遍性。我们通过解决两种传统反对在统计机构中使用贝叶斯方法的传统反对意见。

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