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Latent features with maximal correlation between two equal sets of variables
Author(s) -
Henrion René,
Henrion Günter
Publication year - 1990
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1180040209
Subject(s) - canonical correlation , covariance , mathematics , correlation , latent variable , covariance matrix , statistics , linear correlation , feature (linguistics) , canonical analysis , geometry , philosophy , linguistics
If in two data tables X and Y objects are characterized by the same variables (measured at different occasions), then looking for common latent features should be more appropriate than choosing latent features in X and Y separately (e.g. as in canonical correlation or PLS). The procedure to be proposed here is a slight modification of the method of linear characteristics (according to De Groot and Li) by disclaiming the assumption of equal inner‐block covariance matrices. In order to find weights defining a latent feature with maximal correlation between X and Y , a system of non‐linear equations has to be solved. The procedure is applied to the investigation of heavy metal concentrations in different human tissues.