文章基本信息

标题：Population Synthesis with Quasirandom Integer Sampling
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作者：Andrew Smith ; Robin Lovelace ; Mark Birkin 等
期刊名称：Journal of Artificial Societies and Social Simulation
印刷版ISSN：1460-7425
出版年度：2017
卷号：20
期号：4
页码：1-15
DOI：10.18564/jasss.3550
出版社：University of Surrey, Department of Sociology
摘要：Established methods for synthesising a population from geographically aggregated data are robust and well understood. However, most rely on the potentially detrimental process of integerisation if a wholeindividual population is required, e.g. for use in agent-based modelling (ABM). This paper describes and investigates the use of quasirandom sequences to sample populations from known marginal constraints whilst preserving those marginal distributions. We call this technique Quasirandom Integer Without-replacement Sampling (QIWS) and show that the statistical properties of quasirandomly sampled populations to be superior to those of pseudorandomly sampled ones in that they tend to yield entropies much closer to populations generated using the entropy-maximising iterative proportional fitting (IPF) algorithm. The implementation is extremely eicient, easily outperforming common IPF implementations. It is freely available as an open source R package called humanleague. Finally, we suggest how the current limitations of the implementation can be overcome, providing a direction for future work.
关键词：Microsynthesis; Microsimulation; Quasirandom Sequences; Sampling