Re: EOF explained variance

"Leandro Calil" <leandro@xxxxxxxxxxxxxxxx> wrote in message <g5g4i9$5rc
$1@xxxxxxxxxxxxxxxxxx>...
Dear Roger,
First, thanks for your help !!
I intend make a EOF analysis from a grid space that have 126
points and 8036 times.
I think the right matrix organization for calculate the
covariance matrix from my data is X(8036,126). Is that right??
If it is right, I need to calculate cov(X). It is not this?
I need the total data variance. I hope reach this with the
sum of principal diagonal of my covariance matrix.
Thank you again...
Leandro

It isn't clear to me what you mean by "a grid space that have 126 points and
8036 times". You can clear things up by telling us what size you expect your
covariance matrix to have. Would it be 8036 by 8036 or would it be 126 by
126? I am guessing it would be 126 by 126.

I don't believe you need to calculate the covariance matrix to do your
empirical orthogonal function analysis (also known as principal component
analysis.) Just use the 'svd' (singular value decomposition) function directly
on your data matrix with each row being an observation, (no doubt invoking
the "economy size" option to avoid a 8036 x 8036 size matrix.) This will
automatically give you the orthogonal bases in descending sizes of singular
values.

Roger Stafford

.

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