[R] How to determine the number of dominant eigenvalues in PCA
Fred
fzh113 at hecky.it.northwestern.edu
Mon Jun 28 19:14:52 CEST 2004
Thanks, Prof Ripley
However, I searched some references on scree plot
On deciding the number of dominant eigenvalues, and
Found that this is still a subjective method.
That is, no explicit way or formulation to choose
the number from the 2-D scree plot.
Am I right?
Fred
-----Original Message-----
From: Prof Brian Ripley [mailto:ripley at stats.ox.ac.uk]
Sent: Monday, June 28, 2004 10:24 AM
To: Fred
Cc: R-help mailing list
Subject: Re: [R] How to determine the number of dominant eigenvalues in
PCA
On Mon, 28 Jun 2004, Fred wrote:
> 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.
The short answer is `no' since it depends what you want to do PCA for
(and
there are many possible uses).
> 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.
It's not a curve! If you joins the points by line it is piecewise
linear
and has curvature nowhere.
See ?screeplot and its references, since the plot is called a `scree
plot'. It's a well known technique in all good textbooks on PCA.
> But I could not find any reference papers on this idea.
> Does anyone has tried this method or knows more details on this?
--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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