Discarding Variables in a Principal Component Analysis. I: Artificial Data

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ID: 300991
1972
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Abstract
Often, results obtained from the use of principal component analysis are little changed if some of the variables involved are discarded beforehand. This paper examines some of the possible methods for deciding which variables to reject and these rejection methods are tested on artificial data containing variables known to be “redundant”. It is shown that several of the rejection methods, of differing types, each discard precisely those variables known to be redundant, for all but a few sets of data.
Reference Key
openalex_W2797320655 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ian T. Jolliffe
Journal Journal of the Royal Statistical Society Series C (Applied Statistics)
Year 1972
DOI
10.2307/2346488
URL
https://doi.org/10.2307/2346488
Keywords Keywords not found

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