R help - May 2012 - 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(without using* princomb* command), and
found PCs but this value is different from *'pca$loadings'*.

           But I can find the approximate standardized data, 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
J R F, IIT DELHI

	[[alternative HTML version deleted]]

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]]