mutualinf: An R Package for Computing and Decomposing the Mutual Information Index of Segregation

IF 2.3 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS R Journal Pub Date : 2023-11-01 DOI:10.32614/rj-2023-047
Rafael Fuentealba-Chaura, Daniel Guinea-Martin, Ricardo Mora, Julio Rojas-Mora
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Abstract

In this article, we present the R package [mutualinf](https://CRAN.R-project.org/package=mutualinf) for computing and decomposing the mutual information index of segregation by means of recursion and parallelization techniques. The mutual information index is the only multigroup index of segregation that satisfies strong decomposability properties, both for organizational units and groups. The [mutualinf](https://CRAN.R-project.org/package=mutualinf) package contributes by (1) implementing the decomposition of the mutual information index into a "between" and a "within" term; (2) computing, in a single call, a chain of decompositions that involve one "between" term and several "within" terms; (3) providing the contributions of the variables that define the groups or the organizational units to the overall segregation; and (4) providing the demographic weights and local indexes employed in the computation of the "within" term. We illustrate the use of [mutualinf](https://CRAN.R-project.org/package=mutualinf) using Chilean school enrollment data. With these data, we study socioeconomic and ethnic segregation in schools.
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一个计算和分解分离互信息索引的R包
在本文中,我们提出了R包[mutualinf](https://CRAN.R-project.org/package=mutualinf),用于通过递归和并行化技术计算和分解隔离的互信息索引。互信息指标是唯一满足组织单位和群体强可分解性的多组分离指标。[mutualinf](https://CRAN.R-project.org/package=mutualinf)包的贡献在于(1)将互信息索引分解为“between”和“within”项;(2)在单个调用中计算包含一个“between”项和多个“within”项的分解链;(3)提供定义组或组织单位的变量对整体隔离的贡献;(4)提供计算“内”项时使用的人口权重和地方指标。我们使用智利的学校入学数据来说明[mutualinf](https://CRAN.R-project.org/package=mutualinf)的使用。有了这些数据,我们研究了学校中的社会经济和种族隔离。
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来源期刊
R Journal
R Journal COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.70
自引率
0.00%
发文量
40
审稿时长
>12 weeks
期刊介绍: The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that should be of interest to users or developers of R. The R Journal intends to reach a wide audience and have a thorough review process. Papers are expected to be reasonably short, clearly written, not too technical, and of course focused on R. Authors of refereed articles should take care to: - put their contribution in context, in particular discuss related R functions or packages; - explain the motivation for their contribution; - provide code examples that are reproducible.
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