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Shrunken Estimators in Discriminant and Canonical Variate Analysis
Author(s) -
Campbell Norm A.
Publication year - 1980
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 - 10.2307/2346404
Subject(s) - random variate , linear discriminant analysis , estimator , statistics , discriminant , mathematics , artificial intelligence , psychology , econometrics , computer science , random variable
S ummary Shrunken estimators in canonical variate analysis are shown to lead to improved stability of the resulting coefficients when the between‐groups sum of squares for a particular principal component defined by the within‐groups covariance or correlation matrix is small and the corresponding eigenvalue is also small.