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parsec - Partial Orders in Socio-Economics

Implements tools for the analysis of partially ordered data, with a particular focus on the evaluation of multidimensional systems of indicators and on the analysis of poverty. References, Fattore M. (2016) <doi:10.1007/s11205-015-1059-6> Fattore M., Arcagni A. (2016) <doi:10.1007/s11205-016-1501-4> Arcagni A. (2017) <doi:10.1007/978-3-319-45421-4_19>.

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2.22 score 1 stars 1 dependents 55 scripts 595 downloads

POSetR - Partially Ordered Sets in R

Provides a set of basic tools for generating, analyzing, summarizing and visualizing finite partially ordered sets. In particular, it implements flexible and very efficient algorithms for the extraction of linear extensions and for the computation of mutual ranking probabilities and other user-defined functionals, over them. The package is meant as a computationally efficient "engine", for the implementation of data analysis procedures, on systems of multidimensional ordinal indicators and partially ordered data, in the spirit of Fattore, M. (2016) "Partially ordered sets and the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-015-1059-6>, and Fattore M. and Arcagni, A. (2018) "A reduced posetic approach to the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-016-1501-4>.

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cpp

1.30 score 2 stars 4 scripts 319 downloads

HOasso - Higher Order Assortativity for Complex Networks

Allows to evaluate Higher Order Assortativity of complex networks defined through objects of class 'igraph' from the package of the same name. The package returns a result also for directed and weighted graphs. References, Arcagni, A., Grassi, R., Stefani, S., & Torriero, A. (2017) <doi:10.1016/j.ejor.2017.04.028> Arcagni, A., Grassi, R., Stefani, S., & Torriero, A. (2021) <doi:10.1016/j.jbusres.2019.10.008> Arcagni, A., Cerqueti, R., & Grassi, R. (2023) <doi:10.48550/arXiv.2304.01737>.

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1.00 score 171 downloads

ineqJD - Inequality Joint Decomposition

Computes and decomposes Gini, Bonferroni and Zenga 2007 point and synthetic concentration indexes. Decompositions are intended: by sources, by subpopulations and by sources and subpopulations jointly. References, Zenga M. M.(2007) <doi:10.1400/209575> Zenga M. (2015) <doi:10.1400/246627> Zenga M., Valli I. (2017) <doi:10.26350/999999_000005> Zenga M., Valli I. (2018) <doi:10.26350/999999_000011>.

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1.00 score 1 stars 156 downloads