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# generals
Slackbot
07/25/2023, 8:08 PMThis message was deleted.
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Max (Nixtla)
07/25/2023, 8:23 PMThanks a lot!
You can do that using the order parameter of the Arima model.
https://nixtla.github.io/statsforecast/src/core/models.html#arima-family
Max (Nixtla)
07/25/2023, 8:23 PM# ARIMA Model
arima = ARIMA(order=(1, 1, 1), season_length=1)Max (Nixtla)
07/25/2023, 8:24 PMThen
arima = arima.fit(y=df["y"].values)y_hat_dict = arima.predict(h=6)l
Lewis Livingston
07/25/2023, 8:37 PMFantastic! Thank you! Is there a similar argument for the other available models such as holt winters? I see an "Alpha" argument for exponential smoothing but I don't see a Beta argument for Holt's method.
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Max (Nixtla)
07/25/2023, 9:26 PM@Mariana Menchero?
m
Mariana Menchero
07/25/2023, 9:42 PMHi @Lewis Livingston there's no beta argument because this implementation of Holt's method is the corresponding best ETS model with either additive or multiplicative errors. Hence, the class only takes the following arguments:
Holt (season_length:int=1, error_type:str='A', alias:str='Holt')Mariana Menchero
07/25/2023, 9:44 PMsame for Holt-Winters