Hello, I have multivariate data - matrix X with n rows and p columns. I want to do a linear transformation V=XA similar to PCA but maximizing the Kurtosis instead of the variance. The purpose is to identify potential outliers. I have seen this paper (section 3.1) http://halweb.uc3m.es/esp/Personal/personas/dpena/articles/finaljasa.pdf but the result didnt give me orthogonal components.
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