Principal components selection given extensively many variables

Nils Lehmann

Statistics & Probability Letters, 2005, vol. 74, issue 1, 51-58

Abstract: Principal components analysis relates to the eigenvalue distribution of Wishart matrices. Given few observations and very many variables this distribution maps to eigenvalue statistics in the Gaussian orthogonal ensemble. Principal components selection can then be based on existing analytical results.

Keywords: Principal; components; analysis; Random; matrix; theory (search for similar items in EconPapers)
Date: 2005
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