synthACS: Spatial Microsimulation Modeling with Synthetic American Community Survey Data

IF 5.4 2区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Statistical Software Pub Date : 2022-01-01 DOI:10.18637/jss.v104.i07

Alex P. Whitworth

引用次数: 3

Abstract

synthACS is an R package that provides flexible tools for building synthetic micro-datasets based on American Community Survey (ACS) base tables, allows data-extensibility and enables to conduct spatial microsimulation modeling (SMSM) via simulated annealing. To our knowledge, it is the first R package to provide broadly applicable tools for SMSM with ACS data as well as the first SMSM implementation that uses unequal probability sampling in the simulated annealing algorithm. In this paper, we contextualize these developments within the SMSM literature, provide a hands-on user-guide to package synthACS , present a case study of SMSM related to population dynamics, and note areas for future research.

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synthACS:空间微模拟建模与综合美国社区调查数据

synthACS是一个R包，它提供了基于美国社区调查(ACS)基表构建合成微数据集的灵活工具，允许数据可扩展性，并能够通过模拟退火进行空间微模拟建模(SMSM)。据我们所知，它是第一个为具有ACS数据的SMSM提供广泛适用工具的R包，也是第一个在模拟退火算法中使用不等概率抽样的SMSM实现。在本文中，我们在SMSM文献中对这些发展进行了背景介绍，提供了包synthACS的动手用户指南，提出了与人口动态相关的SMSM案例研究，并指出了未来研究的领域。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Statistical Software 工程技术-计算机：跨学科应用

CiteScore

10.70

自引率

1.70%

发文量

审稿时长

6-12 weeks

期刊介绍： The Journal of Statistical Software (JSS) publishes open-source software and corresponding reproducible articles discussing all aspects of the design, implementation, documentation, application, evaluation, comparison, maintainance and distribution of software dedicated to improvement of state-of-the-art in statistical computing in all areas of empirical research. Open-source code and articles are jointly reviewed and published in this journal and should be accessible to a broad community of practitioners, teachers, and researchers in the field of statistics.