For extracting causal DAG from a time series data, I have read some papers that utilize MLP/LSTM as well as other algorithms. But due to ease of use, I want to use the TETRAD software. But I am not understanding I how to input a time series data like a stock exchange or hospital emergency data in the software. For example, here is a sample of the data I am using. I am facing problem to make the software understand that the data has temporal aspects and it needs to model the data as a time series data to extract the causal relationship DAG. I am not finding proper instructions on which algorithm to use in TETRAD for time series causal relationship extraction as well as how to model the data. As causal inference is not my primary field of study, any guidance will be helpful.
I tried using the FGES algorithm to extract the relationship but I am not sure if that is the correct way.
