An Extended Rao-Stirling Diversity Index to Handle Missing Data

A collection of functions to compute the Rao-Stirling diversity index (Porter and Rafols, 2009) and its extension to acknowledge missing data (i.e., uncategorized references) by calculating its interval of uncertainty using mathematical optimization as proposed in Calatrava et al. (2016) . The Rao-Stirling diversity index is a well-established bibliometric indicator to measure the interdisciplinarity of scientific publications. Apart from the obligatory dataset of publications with their respective references and a taxonomy of disciplines that categorizes references as well as a measure of similarity between the disciplines, the Rao-Stirling diversity index requires a complete categorization of all references of a publication into disciplines. Thus, it fails for a incomplete categorization; in this case, the robust extension has to be used, which encodes the uncertainty caused by missing bibliographic data as an uncertainty interval. Classification / ACM - 2012: Information systems ~ Similarity measures, Theory of computation ~ Quadratic programming, Applied computing ~ Digital libraries and archives.


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1.0-5 by Maria del Carmen Calatrava Moreno, 2 years ago

Browse source code at

Authors: Maria del Carmen Calatrava Moreno [aut, cre] , Thomas Auzinger [aut]

Documentation:   PDF Manual  

Task views: Missing Data

GPL-3 license

Imports doParallel, gmp, iterpc, quadprog, igraph, foreach

See at CRAN