Question: I have been training ARIMA models using the statsmodels (v0.12.2) package, and would like to check out how a model fits on the training data

#### Current Code:

```
from statsmodels.tsa.arima.model import ARIMA

#for some p,d,q
model = ARIMA(train, order = (p,d,q)
model_fit = model.fit()

```

#### Attempting to do:

I would like to plot the predictions of the training set against the actual training values.   

I have been trying to use the following after reading [this documentation](https://www.statsmodels.org/stable/generated/statsmodels.tsa.arima.model.ARIMAResults.get_prediction.html):

```
model_fit.get_prediction()

```

However, this returns:

```
<statsmodels.tsa.statespace.mlemodel.PredictionResultsWrapper at 0x7f804bf5bbe0>

```

#### Question:

How can I return these predicted values for the training set?

Advice appreciated!

Answer: 
I think you are looking for the fitted values of the model, if so then use,

```
model_fit.fittedvalues

```

You can find a complete example [here](https://www.statsmodels.org/stable/generated/statsmodels.tsa.arima.model.ARIMAResults.append.html?highlight=arima).
I've found that changing:

```
model_fit.get_prediction()

```

to

```
model_fit.get_prediction().predicted_mean

```

returns an array which isnt perfect but suitable for my analysis.

Please post an answer if you have an alternative/better method!