论文标题
从澳大利亚人口普查数据中建立大量的合成人群
Building a large synthetic population from Australian census data
论文作者
论文摘要
我们介绍了从澳大利亚的人口普查数据中创建合成人群的工作，该人口应用于大墨尔本地区。我们使用一种无样本的方法来进行人群合成，该方法不依赖于原始人群的样本。我们算法的输入是来自所需的人级和家庭级别属性的人口普查的联合边际分布，输出是一组逗号分隔值（.CSV）文件，其中包含家庭中独特个人的完整合成人群；随着年龄，性别，关系状况，家庭类型和规模，与人口普查数据相匹配。我们的算法有效，它可以在三分钟内在现代计算机上为墨尔本创建合成人口，其中包括180万户家庭的450万人。该算法的代码托管在GitHub上。
We present work on creating a synthetic population from census data for Australia, applied to the greater Melbourne region. We use a sample-free approach to population synthesis that does not rely on a disaggregate sample from the original population. The inputs for our algorithm are joint marginal distributions from census of desired person-level and household-level attributes, and outputs are a set of comma-separated-value (.csv) files containing the full synthetic population of unique individuals in households; with age, gender, relationship status, household type, and size, matched to census data. Our algorithm is efficient in that it can create the synthetic population for Melbourne comprising 4.5 million persons in 1.8 million households within three minutes on a modern computer. Code for the algorithm is hosted on GitHub.
