生成一个双层合成人口为法国直辖市:结果和评价四种合成重建方法

B. Yameogo, P. Vandanjon, Pascal Gastineau, P. Hankach
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引用次数: 5

摘要

本文详细描述了法国市政当局家庭和个人两层合成人口的生成。以法国人口普查数据为例,采用了四种综合重建方法和两种概率积分方法。本文通过一个通用框架对每种方法进行了深入的描述。然后根据各种标准对这些方法进行比较。结果表明,所测试的算法能生成真实的合成种群,其中最有效的合成重建方法是层次迭代比例拟合和相对熵最小化算法。结合截断复制抽样分配方法进行整合,这些算法生成的家庭级和个人级数据的值最接近实际人口的值。采用四个指标:R SAE,所有好的结果,a特征到一些拟合的步骤,最小化(HIPF)的步骤,
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generating a Two-Layered Synthetic Population for French Municipalities: Results and Evaluation of Four Synthetic Reconstruction Methods
: This article describes the generation of a detailed two-layered synthetic population of households and individuals for French municipalities. Using French census data, four synthetic reconstruction methods associated with two probabilistic integerization methods are applied. The paper offers an in-depth description of each method through a common framework. A comparison of these methods is then carried out on the basis of various criteria. Results showed that the tested algorithms produce realistic synthetic populations with the most efficient synthetic reconstruction methods assessed being the Hierarchical Iterative Proportional Fitting and the relative entropy minimization algorithms. Combined with the Truncation Replication Sampling allocation method for performing integerization, these algorithms generate household-level and individual-level data whose values lie closest to those of the actual population. using four indicators: R SAE, all good results, a characteristics to the some the fitting step, minimization (HIPF) the step,
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