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I am currently experimenting with the granger_lasso algorithm provided in the repository.
Given that one time series has N dimensions, and the time lag is equal to T.
The shape of the output of granger_lasso is [N, N * T].
May I know how I should interpret this and convert it into a [T, N, N] matrix where, along the time lag dimension, the matrix [N, N] represents the influence of the i-th node on the j-th node.
Thank you!
The text was updated successfully, but these errors were encountered:
Hi, thanks for the great work.
I am currently experimenting with the granger_lasso algorithm provided in the repository.
Given that one time series has N dimensions, and the time lag is equal to T.
The shape of the output of granger_lasso is [N, N * T].
May I know how I should interpret this and convert it into a [T, N, N] matrix where, along the time lag dimension, the matrix [N, N] represents the influence of the i-th node on the j-th node.
Thank you!
The text was updated successfully, but these errors were encountered: