How to Compute Tri-Coherence from Time-Series Data?

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To compute tri-coherence from time-series data, existing libraries or software specifically for this purpose are scarce, prompting the need for custom code. While bicoherence tools are more common, tri-coherence calculations require specialized approaches. Users are encouraged to code their own solutions to ensure accuracy in their calculations. Benchmarking against synthetic data is recommended for validating results. The discussion highlights the challenges in finding ready-made solutions for tri-coherence analysis.
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Dear all,

I have time-series data, from which I would like to compute the tricoherence. After some googling, it seems that I will have to write my own code. But before I begin, let me ask this.

Do anyone here know of a code, library (fortran, c), module (python, matlab, IDL, mathematica) or software to compute a tri-coherence?

Thank you!
 
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Not just the bicoherence, but the tricoherence?
 
Yes indeed, tri, not bi.
 
I see. I don't know of such a package offhand, but this is specialized enough that you might want to code it yourself anyway, just to be sure what is going into your calculation.

Out of curiosity, what sort of problem are you working on (if you wouldn't mind sharing)?
 
You're right, I'd better code it anyway. But a package would be helpful to benchmark against my own code.

Sorry, I can't share my project before we have some paper out. I'll try to answer to you in a few months.
 
Ok. I suggest using processing synthetic data as the best benchmark. Well good luck!
 
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