Am I correct to understand from the previous discussions on this topic (a
few years back) that if I have a matrix with missing values my PCA options
seem dismal if:

 

(1)     I don’t want to impute the missing values.

(2)     I don’t want to completely remove cases with missing values.

(3)     I do cov() with use=”pairwise.complete.obs”, as this produces
negative eigenvalues (which it has in my case!).

 

This seems like such a shame as I would like to use PCA to plot my
clustering results. Any wisdom?

 

Quin

 

 

 


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