41108 # How to get constant term in AR Model with statsmodels and Python?

I'm trying to model my time series data using the AR model.

<img src="https://i.stack.imgur.com/U63s7.png" alt="enter image description here">

This is the code that I'm using.

```# Compute AR-model (data is a python list of number) model = AR(data) result = model.fit() plt.plot(data, 'b-', label='data') plt.plot(range(result.k_ar, len(data)), result.fittedvalues, 'r-') plt.show() ```

I've successfully get the p value using `result.k_ar`, parameter with `result.params`, epsilon term with `result.sigma2`. The problem is that I can't find a way to get the c (constant) term. Here is the code I write to compare the result.

```# Plot fit = [] for t in range(result.k_ar, len(data)): value = 0 for i in range(1, result.k_ar+1): value += result.params[i-1] * data[t - i] fit.append(value) plt.plot(data, 'b-', label='data') plt.plot(range(result.k_ar, len(data)), fit, 'r-', label='fit') plt.plot(range(result.k_ar, len(data)), result.fittedvalues, 'r-') plt.show() ```

My result and the result from `result.fittedvalues` confirm my evident that there is some constant term added to the model. Thanks.

<img src="https://i.stack.imgur.com/VekrS.png" alt="enter image description here">

The constant is the zero-th element in params. E.g., params.

```fit = [] for t in range(result.k_ar, len(data)): value = result.params for i in range(2, result.k_ar + 2): value += result.params[i - 1] * data[t - i + 1] fit.append(value) ```
```np.dot(result.model.X, result.params) ```
```constant = mean(1 - arparams.sum()) ```