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

Abstract:

In this article, we present the R 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 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 using Chilean school enrollment data. With these data, we study socioeconomic and ethnic segregation in schools.

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Published

Nov. 1, 2023

Received

Jan 18, 2022

DOI

10.32614/RJ-2023-047

Volume

Pages

15/2

77 - 88


0.1 Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2023-047.zip

Footnotes

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    Citation

    For attribution, please cite this work as

    Fuentealba-Chaura, et al., "mutualinf: An R Package for Computing and Decomposing the Mutual Information Index of Segregation", The R Journal, 2023

    BibTeX citation

    @article{RJ-2023-047,
      author = {Fuentealba-Chaura, Rafael and Guinea-Martin, Daniel and Mora, Ricardo and Rojas-Mora, Julio},
      title = {mutualinf: An R Package for Computing and Decomposing the Mutual Information Index of Segregation},
      journal = {The R Journal},
      year = {2023},
      note = {https://doi.org/10.32614/RJ-2023-047},
      doi = {10.32614/RJ-2023-047},
      volume = {15},
      issue = {2},
      issn = {2073-4859},
      pages = {77-88}
    }