Hi
I have tried to google and read various threads for days now, but unfortunately, I could not find an answer on the following issue...
I am trying to do some STATA procedures (e.g. the correlogram) to analyse my data and to construct a forecast by the ARIMA model, but STATA states that my data sample includes multiple panels.
I interpreted it as STATA thinks my dataset is a panel data. Therefore, I removed all variables besides the one I want to study along with a time variable, but it did not help on the issue. I am not sure what to do, to be able to make the correlogram and additional procedures to construct my ARIMA model. My data is weekly from 2021-2023, and it contains one unit after the remaining variables are removed from the data.
Furthermore, I want to ask if it is even possible to do an ARIMA forecast with panel data? If yes, can I then use the procedures for time series after I define my data with tsset? Also, is it possible to use the arimaauto code?
Thank you in advance, and I hope it makes sense.
Best,
Maria
I have tried to google and read various threads for days now, but unfortunately, I could not find an answer on the following issue...
I am trying to do some STATA procedures (e.g. the correlogram) to analyse my data and to construct a forecast by the ARIMA model, but STATA states that my data sample includes multiple panels.
I interpreted it as STATA thinks my dataset is a panel data. Therefore, I removed all variables besides the one I want to study along with a time variable, but it did not help on the issue. I am not sure what to do, to be able to make the correlogram and additional procedures to construct my ARIMA model. My data is weekly from 2021-2023, and it contains one unit after the remaining variables are removed from the data.
Furthermore, I want to ask if it is even possible to do an ARIMA forecast with panel data? If yes, can I then use the procedures for time series after I define my data with tsset? Also, is it possible to use the arimaauto code?
Thank you in advance, and I hope it makes sense.
Best,
Maria
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