## arima.arima()


Fit ARIMA model and generate forecast.


Usage

``` python
arima.arima(
    train,
    params,
    test=None,
    horizon=None,
)
```


## Parameters


`train: pd.DataFrame`  
Historic training data.

`params: ARIMAParams`  
Parameters controlling the model.

`test: pd.DataFrame | None = None`  
Data containing the dates to forecast in a `ds` column. Typically a held-out test set or cross-validation fold.

`horizon: int | None = None`  
Number of days to forecast, after the final date in `train`. To be used if there is no test set (e.g., if actually predicting into future with no data to compare against).


## Returns


`forecast: pd.DataFrame`  
Forecast dataframe.