Robust principal component analysis in Stata
AbstractWhen 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Stata Users Group in its series United Kingdom Stata Users' Group Meetings 2009 with number 02.
Date of creation: 16 Sep 2009
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-09-19 (All new papers)
You can help add them by filling out this form.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F Baum).
If references are entirely missing, you can add them using this form.