随机总体分析:一种功能数据方法

Lei Fang, W. Härdle
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引用次数: 8

摘要

本文在人口预测基准李-卡特(Lee-Carter, LC)模型的基础上,提出了各种扩展和修正。我们研究了其中一种扩展,Hyndman-Ullah (HU)方法,并将其应用于亚洲人口数据集:中国、日本和台湾。它结合了功能主成分分析(fPCA)、非参数平滑和时间序列分析的思想。基于这种随机方法,计算和比较了亚洲不同地区的人口特征和趋势。我们举例说明,中国和日本在过去十年中表现出类似的人口趋势。我们还将HU方法与LC模型进行了比较。当我们有高质量的数据时,HU方法可以解释更多的人口动态变化,然而,当我们处理有限和稀缺的数据集时,它也会遇到问题,并且由于数据质量不合格和人口政策,它的表现与LC模型相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic Population Analysis: A Functional Data Approach
Based on the Lee-Carter (LC) model, the benchmark in population forecasting, a variety of extensions and modifications are proposed in this paper. We investigate one of the extensions, the Hyndman-Ullah (HU) method and apply it to Asian demographic data sets: China, Japan and Taiwan. It combines ideas of functional principal component analysis (fPCA), nonparametric smoothing and time series analysis. Based on this stochastic approach, the demographic characteristics and trends in different Asian regions are calculated and compared. We illustrate that China and Japan exhibited a similar demographic trend in the past decade. We also compared the HU method with the LC model. The HU method can explain more variation of the demographic dynamics when we have data of high quality, however, it also encounters problems and performs similarly as the LC model when we deal with limited and scarce data sets, such as Chinese data sets due to the substandard quality of the data and the population policy.
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