Dear All,

I want to know if there is some easy and reliable way
to estimate the number of dominant eigenvalues
when applying PCA on sample covariance matrix.

Assume x-axis is the number of eigenvalues (1, 2, ....,n), and y-axis is the 
corresponding eigenvalues (a1,a2,..., an) arranged in desceding order.
So this x-y plot will be a decreasing curve. Someone mentioned using the elbow (knee) method
to find the point that the maximal curvature of this curve occurs.
The number at this point would be the number of dominant eigenvalues.

But I could not find any reference papers on this idea.
Does anyone has tried this method or knows more details on this?

Thanks for your point.

Fred

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