  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.
