Nixtla's Open Source Time Series Ecosystem.

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hi <@U04AMQ5C6AJ>

You can use the `arima_string`  function. Here’s an example,

sf = StatsForecast(
    df=all_leads_weekly_exo_train,
    models=[AutoARIMA(season_length=52)],
    freq='W',
    n_jobs=-1)

arima_string(sf.models[0].model_)

```AttributeError: 'AutoARIMA' object has no attribute 'model_'```


Doesn't seem to work this way, are there two AutoARIMA objects?

To access the fitted models’ information, you must call the `fit`  method first. This method will generate the `fitted_`  attribute, which contains the fitted models. Then you could call `arima_string`  on the specific model and time series. Here’s an example,