# Using kurtosis to assess significance of components from independent component analysis

In PCA eigenvalues determine the order of components. In ICA I am using kurtosis to obtain the ordering. What are some accepted methods to assess the number, (given I have the order) of components that are singificant apart from prior knowledge about the signal?

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I actually think that in ICA you can still use the number of 'significant' (ie, 90% of energy) eigen-vectors, as the number of independent components. –  Tarantula Aug 29 '12 at 15:27