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SGL: Stata Graph Library for network analysis

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  • Hirotaka Miura

    ()
    (Federal Reserve Bank of San Francisco)

Abstract

Network analysis is becoming a popular field of research. Though sophisticated packages exist for analyzing networks, such as sna, igraph, and RBGL packages developed for R and MatlabBGL implemented in Matlab, similar programs have yet to be written for Stata. I attempt to fill this void by designing the Stata Graph Library (SGL) in Mata which consists of functions that construct network centrality measures, metrics, and matrices. SGL retrieves relational data from an edge list defined by existing Stata variables or from matrices stored in Mata. SGL is built to work within Stata version 11.1 and is intended for both directed and undirected networks, either of which can be weighted by positive values or unweighted. This paper provides a brief overview of concepts related to network analysis and introduces Stata Graph Library functions that generate matrix representations, centrality measures, and clustering coefficients for directed or undirected networks with or without positive weights.

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File URL: http://fmwww.bc.edu/repec/chic2011/chi11_miura.pdf
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File URL: http://fmwww.bc.edu/repec/chic2011/chi11_miura_SGL_version_1.1.2.zip
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Bibliographic Info

Paper provided by Stata Users Group in its series CHI11 Stata Conference with number 7.

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Date of creation: 20 Jul 2011
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Handle: RePEc:boc:chic11:7

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Web page: http://stata.com/meeting/chicago11/
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  1. Rense Corten, 2011. "Visualization of social networks in Stata using multidimensional scaling," Stata Journal, StataCorp LP, vol. 11(1), pages 52-63, March.
  2. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer, vol. 18(1), pages 39-43, March.
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Cited by:
  1. Hale, Galina, 2012. "Bank relationships, business cycles, and financial crises," Journal of International Economics, Elsevier, vol. 88(2), pages 312-325.

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