Hi all,
Let's say we have M x N matrix, which represents N time series, each having
M observations in order of time.
How do we find maximal number of linear combinations of these N time series,
their mutual correlation has to be less than certain pre-specified
constraints.
That's to say, we would like to find as many combinations of the N time
series as possible, such that their mutual correlation remains below a
bound.
Our understanding is that with the help from PCA, we will be able to find
probably N such combinations, expressed in the form of eigenvectors, such
that the N resultant newly constructed time series have 0 correlation
(orthogonal).
But we now want to relax the problem from 0 correlation to within a certain
bound.
Your thoughts and pointers are highly appreciated. Thank you!
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