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January 1, 1994Journal of the Royal Statistical Society Series D (The Statistician)

Diagnostics for Principal Components: Influence Functions as Diagnostic Tools

Stephen P. Brooks

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Abstract

Care should be taken when interpreting the results of a principal components analysis. As an aid to interpretation and as a guide to reliability, a range of diagnostic tools have been proposed. This paper introduces and reviews recent work on influence functions, as well as introducing new methodology, and highlights their use as diagnostic tools for principal components analysis. A Monte Carlo approach is used to assess significance for the influence values obtained.

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Stephen P. Brooks (1994) studied this question.

synapsesocial.com/papers/6a9e1651031501fc02c7cdbf https://doi.org/10.2307/2348133

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