Hi! There is a chapter in the book from H�rdl 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 *********** REPLY SEPARATOR *********** 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? > >Thanks for your point. > >Fred > > [[alternative HTML version deleted]] > >______________________________________________ >[EMAIL PROTECTED] mailing list >https://www.stat.math.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
