which script consists of kernel granger casuality function?

[manvirvirk]

[danielemarinazzo]

causality.m is the main function, it calls other ones.

[manvirvirk]

Thanks for the information, i could use it now. I have one more query how to apply granger causality for non-stationary signals as it is meant that it can be applied only for stationary signals.

[danielemarinazzo]

If your time series do not satisfy the stationarity criterion of your choice, then you should use a sliding window (if you have enough samples per window and/or multiple trials), or use another time varying approach.

[manvirvirk]

@danielemarinazzo i have non stationary brain signal with several trials. I have filtered it and windowed it into 2s segment. After this i got matrix of 500 by 35 to which i applied granger to select columns . Is this the way you you are saying?

[danielemarinazzo]

and where are you using the trials? what is 500 and what is 35?

[manvirvirk]

@danielemarinazzo 500 are trials and 35 are number of channels of brain signals

[danielemarinazzo]

This indeed allows you to perform a time point by time point analysis, but not Granger causality since all data refers to the same time point. The minimal window should be equal to the order of your auto regressive model plus one.

On Thu, 23 Nov 2023, 15:23 manvirvirk, @.***> wrote:

@danielemarinazzo https://github.com/danielemarinazzo 500 are trials and 35 are number of channels of brain signals

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[manvirvirk]

@danielemarinazzo does this repo, causality.m find the granger causality or not?

[danielemarinazzo]

the repo or the function? The function causality.m computes Granger causality indeed.

On Thu, 23 Nov 2023 at 18:20, manvirvirk @.***> wrote:

@danielemarinazzo https://github.com/danielemarinazzo does this repo, causality.m find the granger causality or not?

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[manvirvirk]

ok thank you for the help @danielemarinazzo (y)