Tenreiro Machado J A, Lopes António M
Department of Electrical Engineering, Institute of Engineering, Polytechnic of Porto, Rua Dr. António Bernardino de Almeida, 431, 4249 - 015 Porto, Portugal.
LAETA/INEGI, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200 - 465 Porto, Portugal.
Nonlinear Dyn. 2021;104(4):3897-3911. doi: 10.1007/s11071-021-06503-2. Epub 2021 May 21.
Uncertainty about the time of death is part of one's life, and plays an important role in demographic and actuarial sciences. Entropy is a measure useful for characterizing complex systems. This paper analyses death uncertainty through the concept of entropy. For that purpose, the Shannon and the cumulative residual entropies are adopted. The first may be interpreted as an average information. The second was proposed more recently and is related to reliability measures such as the mean residual lifetime. Data collected from the Human Mortality Database and describing the evolution of 40 countries during several decades are studied using entropy measures. The emerging country and inter-country entropy patterns are used to characterize the dynamics of mortality. The locus of the two entropies gives a deeper insight into the dynamical evolution of the human mortality data series.
死亡时间的不确定性是人生的一部分,并且在人口统计学和精算科学中起着重要作用。熵是一种用于刻画复杂系统的有用度量。本文通过熵的概念来分析死亡不确定性。为此,采用了香农熵和累积剩余熵。前者可解释为平均信息量。后者是最近提出的,与诸如平均剩余寿命等可靠性度量相关。利用熵度量方法对从人类死亡率数据库收集的、描述40个国家几十年间演变的数据进行了研究。新兴国家和国家间的熵模式被用来刻画死亡率的动态变化。这两种熵的轨迹能更深入地洞察人类死亡率数据序列的动态演变。