Using observed confidence levels to perform principal component analyses
- Alan M. Polansky(corresponding author),
- Northern Illinois University,
Scholary Output:
Contribution to journal
Article
Research
Peer-reviewAbstract
ABSTRACT: This paper focuses on applying the method of observed confidence levels to problems commonly encountered in principal component analyses. In particular, we focus on assigning levels of confidence to the number of components that explain a specified proportion of variation in the original data. Approaches based on the normal model as well as a non parametric model are explored. The usefulness of the methods are discussed using an example and an empirical study.
Publication Information
Output type
Scholary Output:
Contribution to journal
Article
Research
Peer-reviewOriginal language
English (US)Pages from-to (Number of pages)
Pages 3596-3611 (16 pages)Journal (Volume, Issue Number)
Communications in Statistics - Theory and Methods (Volume 45, Issue 12)Publication milestones
- Published - 06/17/2016
Publication status
Published - 06/17/2016
ISSN
0361-0926Publication IDs
- Scopus: 84969972548
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1
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0.50
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1
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0.50
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1
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1
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Author count
2
SciVal
Paper percentile
23
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