The determination of the shapes of mortality curves, the estimation and projection of mortality patterns over time, and the investigation of differences in mortality patterns across different small underdeveloped populations have received special attention in recent years. The challenges involved in this type of problems are the common sparsity and the unstable behavior of observed death counts in small areas (populations). These features impose many dificulties in the estimation of reasonable mortality schedules. In this chapter, we present a discussion about this problem and we introduce the use of relational Bayesian dynamic models for estimating and smoothing mortality schedules by age and sex. Preliminary results are presented, including a comparison with a methodology recently proposed in the literature. The analyzes are based on simulated data as well as mortality data observed in some Brazilian municipalities.
翻译:近年来,人们特别注意确定死亡率曲线的形状,估计和预测长期死亡率模式,调查不同欠发达小人群的死亡率模式差异,这类问题涉及的挑战是小地区(人口)观察到的死亡计数普遍过于拥挤和不稳行为,这些特点在估计合理死亡率时间表方面造成许多损失。在本章中,我们讨论这一问题,并采用关系型巴耶斯动态模型按年龄和性别估算和平滑死亡率时间表。初步结果已经提出,包括与文献中最近提出的方法进行比较。分析以模拟数据以及巴西一些城市观察到的死亡率数据为基础。