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Robust principal component analysis in Stata

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Author Info

  • Vincenzo Verardi

    ()
    (University of Brussels and University of Namur)

Abstract

When some observations are outlying (in one or several dimensions) PCA is distorted an may lead to incorrect results. We therefore propose a simple solution to deal with this problem by providing a short ado file. To illustrate the importance of outliers in PCA I would like to present a simple analysis identifying the underlying factors of academic excellence calling both the classical PCA and the robust PCA and relying on the rankings of Universities.

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File URL: http://repec.org/usug2009/Verardi.ppt
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Bibliographic Info

Paper provided by Stata Users Group in its series United Kingdom Stata Users' Group Meetings 2009 with number 02.

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Date of creation: 16 Sep 2009
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Handle: RePEc:boc:usug09:02

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Web page: http://www.stata.com/meeting/uk09
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