Hi,

Thanks a lot for your comments.  I did try earlier on to remove the bad points 
but came across some problems when re-ordering my array. I will try out the 
method sent to me and check the reference.

Regards, Marjolaine.



>>> <kgdunn+nab...@gmail.com> 02/11/09 4:06 PM >>>
Marjolaine,

I am assuming your masked array entries are missing data.  Multivariate 
analysis with missing data can be handled in several standard ways, however 
these methods don't appear in most Python libraries.

Here are some references on the topic that will help you:

[1] P.R.C. Nelson and J.F. MacGregor, 1996, "Missing data methods in PCA and 
PLS: Score calculations with incomplete observations", Chemometrics and 
Intelligent Laboratory Systems, v35, p 45-65.

[2] F. Arteaga and A. Ferrer, 2002, "Dealing with missing data in MSPC: several 
methods, different interpretations, some examples", Journal of Chemometrics, 
v16, p408-418.

Paper [1] deals with building a model with missing data, while paper [2] looks 
at applying an existing PCA model to new data that contains missing entries.

Hope these help,
Kevin

Marjolaine Rouault wrote:
> 
> Hi,
> 
> I am struggling to do a PCA analysis on a masked array. Anybody has
> suggestions on how to deal with masked array when doing PCAs?
> 
> Best regards, Marjolaine.
>

Quoted from: 
http://www.nabble.com/matplotlib.mlab-PCA-analysis-tp21932808p21932808.html



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