How to Compute the EOFs by SVD?

  • #1
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Main Question or Discussion Point

Considering I have a matrix ##\mathbf{A}## which has a size of ##M \times N##, how can I compute the Empirical Orthogonal Functions (EOFs) by Singular Value Decomposition (SVD)?

According to SVD, the matrix ##\mathbf{A}## is

##\mathbf{A} = \mathbf{U} \mathbf{\Sigma} \mathbf{V}^{T}##

where a superscript of ##T## denotes a transpose. Now, which are the EOFs in this equation, are they the rows of ##\mathbf{V}^{T}## or its columns (the rows of ##\mathbf{V}##)?

Thank you in advance.
 

Answers and Replies

  • #2
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Thanks for the post! This is an automated courtesy bump. Sorry you aren't generating responses at the moment. Do you have any further information, come to any new conclusions or is it possible to reword the post?
 
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