Partial Order Concepts in Applied Sciences pp 275-289 | Cite as
PARSEC: An R Package for Partial Orders in Socio-Economics
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Abstract
Partially ordered sets are getting more important in socio-economical applications. In particular, their application in poverty evaluation (Fattore et al., New perspectives in statistical modeling and data analysis. Springer, Berlin, 2011) shows the advantages of their use in multivariate statistics on ordinal variables. A combinatory approach is necessary to apply this methodology, therefore the development of computational tools about partial orders is required. R is a widespread environment for statistical computing and graphics. The recent publication of the parsec (PARtial orders in Socio-EConomics) package on CRAN (the Comprehensive R Archive Network) is an achievement for the diffusion of computational tools devoted to the applications of partial orders in socio-economics. The package also implements functions related to composite indicators (Fattore et al., Quality of life in Italy. Springer, Berlin, 2012) in order to provide results of different approaches that can be compared. The aim of this work is to explain the functionalities of parsec, through examples and descriptions of its main functions.
Keywords
Comprehensive R Archive Network (CRAN) Partial Order Set Downset Generalized Incidence Matrices TRUE FALSEReferences
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