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Discarding Variables in a Principal Component Analysis. Ii: Real Data
Author(s) -
Jolliffe I. T.
Publication year - 1973
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2346300
Subject(s) - principal component analysis , statistics , component (thermodynamics) , mathematics , econometrics , computer science , thermodynamics , physics
Summary In this paper it is shown for four sets of real data, all published examples of principal component analysis, that the number of variables used can be greatly reduced with little effect on the results obtained. Five methods for discarding variables, which have previously been successfully tested on artificial data (Jolliffe, 1972), are used. The methods are compared and all are shown to be satisfactory for real, as well as artificial, data, although none is shown to be overwhelmingly superior to the others.