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 significant apart from prior knowledge about the signal?
Thank You I will do so immediately
Would You send me a link to Your paper? work so that I have some idea on how to apply it, as my problem is atypical
Johnstone I (2001) On the distribution of the largest eigenvalue in principal components analysis. Ann Stat 29: 295–327
Population Structure and Eigenanalysis, PAterson is also applying the preceding and explains.
the second one is fantastic
what if my n>m, what do I do? what distribution do I use?