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Re: Unable to install Tisean
From: |
Juan Pablo Carbajal |
Subject: |
Re: Unable to install Tisean |
Date: |
Wed, 8 Aug 2018 22:48:38 +0200 |
Hi,
If you only want PCA you do not need tisean at all.
If X is your dataset (rows: samples, cols= variables)
X_ = X - mean (X); # center variables
[U S V] = svd (X_, 1);
PCA_basis = V; # columns are your PCA vectors
P = S * U.'; # These are the scores, such that X_ = V * P
lambda = diag (S).^2 / ( size(X,1) - 1); # Eigenvalues of the sample
covaraince matrix
cumvar = cumsum (lambda) / sum (lambda); # explained variance as
function of number of components
Regards,