# [R] How to determine the number of dominant eigenvalues in PCA

Wolski wolski at molgen.mpg.de
Mon Jun 28 19:36:52 CEST 2004

```Hi!

There is a chapter in the book from Härdl about the interpretation of PCs available online.
http://www.quantlet.com/mdstat/scripts/mva/htmlbook/mvahtmlframe93.html

About determining the number of dominant eigenvalues is a chapter in book of A. Handl  (available online but in german.)
http://www.quantlet.com/mdstat/scripts/mst/html/msthtmlframe56.html

Two references to this topic from this online book.
Cattell, R. B. (1966): The scree test for the number of factors. Multivariate Behavioral Research, 1, 245-276
Kaiser, H. F. (1960): The application of electronic computers to factor analysis. Educ. Psychol. Meas., 20, 141-151

Hope this helps.
Sincerely Eryk

On 28.06.2004 at 10:06 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?
>
>
>Fred
>
>	[[alternative HTML version deleted]]
>
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