Abstract
AbstractIf 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.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call