Dear David,

    Thank you for your time and consideration,

     My data set is Sea Surface temperature (sst) of 50 year monthly global
data (1x1 degree resolution ). My goal is to calculate the EOF1 , EOF2 &
EOF3 at each Lat-Lon location.  How to use 'princomp' command usefully to
calculate these values.


Thanking you all in advance


On Fri, May 18, 2012 at 9:28 PM, David L Carlson <dcarlson@tamu.edu> wrote:

> Check the posting guidelines and give us a small reproducible example using
> dput(). It is here
> http://www.R-project.org/posting-guide.html
>
> You say you want "PCs of a spatial data set (single variable)", but you
> must
> mean something else. It sounds like your variables are highly correlated
> with one another or you have more variables than cases. The function prcomp
> also computes PCs but it uses singular value decomposition rather than
> matrix inversion.
>
> ----------------------------------------------
> David L Carlson
> Associate Professor of Anthropology
> Texas A&M University
> College Station, TX 77843-4352
>
> > -----Original Message-----
> > From: r-help-bounces@r-project.org [mailto:r-help-bounces@r-
> > project.org] On Behalf Of dileep kunjaai
> > Sent: Friday, May 18, 2012 8:01 AM
> > To: r-help@r-project.org
> > Subject: [R] Finding the principal components
> >
> > Dear all,
> >
> >        I am trying to find  the PCs of a spatial data set (single
> > variable).  I want to calculate the PCs at each Lat-Lon location.
> >
> >         The* 'princomp'* command gives the approximate standardized
> > data,
> > (i.e* pca$scores*), stranded deviation ..etc. I tried*
> > 'pca$loadings'*also,  but it giving value 1 all time.
> >
> >           Then I tried manually*(* First calculate correlation matrix
> > (X*X^T), then arranged it's eigen value in descending order, and chose
> > the
> > corresponding eigenvectors (Q_j's),  then pc=X^(T)* Q_j , it will give
> > a
> > single value called first PC as j=1 *)*, and found PCs but this value
> > is
> > different from *'pca$loadings'*.
> >
> >            But I can find the approximate standardized data, (pc1*Q_1)
> > which is similar to *pca$scores*.   But this method is time consuming.
> >
> >           Please help me to tackle this problem.
> >
> >
> >
> >
> > Thank you for all  in advance
> >
> >
> >
> >
> > --
> > DILEEPKUMAR. R
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-
> > guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
>


-- 
DILEEPKUMAR. R
J R F, IIT DELHI

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