Fred wrote:
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
Try this reference from the field of ecology:
@Article{571,
Author = {D. A. Jackson},
Title = {Stopping rules in principal components analysis: a
comparison of heuristic and statistical approaches},
Journal = {Ecology},
Volume = {74},
Number = {8},
Pages = {2204--2214},
month = {},
year = 1993
}
Gav
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Gavin Simpson [T] +44 (0)20 7679 5522
ENSIS Research Fellow [F] +44 (0)20 7679 7565
ENSIS Ltd. & ECRC [E] [EMAIL PROTECTED]
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