Raftery Adrian E, Alkema Leontine, Gerland Patrick
Department of Statistics, Box 354322, University of Washington, Seattle, WA 98195-4322.
Department of Statistics and Applied Probability and Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117546;
Stat Sci. 2014 Feb;29(1):58-68. doi: 10.1214/13-STS419.
The United Nations regularly publishes projections of the populations of all the world's countries broken down by age and sex. These projections are the de facto standard and are widely used by international organizations, governments and researchers. Like almost all other population projections, they are produced using the standard deterministic cohort-component projection method and do not yield statements of uncertainty. We describe a Bayesian method for producing probabilistic population projections for most countries that the United Nations could use. It has at its core Bayesian hierarchical models for the total fertility rate and life expectancy at birth. We illustrate the method and show how it can be extended to address concerns about the UN's current assumptions about the long-term distribution of fertility. The method is implemented in the R packages bayesTFR, bayesLife, bayesPop and bayesDem.
联合国定期发布按年龄和性别细分的世界各国人口预测。这些预测是事实上的标准，被国际组织、政府和研究人员广泛使用。与几乎所有其他人口预测一样，它们是使用标准的确定性队列成分预测方法得出的，并不产生不确定性陈述。我们描述了一种可为联合国能够使用的大多数国家生成概率性人口预测的贝叶斯方法。其核心是用于总和生育率和出生时预期寿命的贝叶斯层次模型。我们阐述了该方法，并展示了如何对其进行扩展以解决对联合国当前关于生育率长期分布假设的担忧。该方法在R包bayesTFR、bayesLife、bayesPop和bayesDem中实现。
