title: rolling polynomial regression in pandas
body: <p>I'm quite new to pandas here, searched but couldn't find an answer if yes or not it's feasible.</p>
  
  <p>so far I'm able to calculate rolling coefficients of a simple regression <code>(Y= coef1 * A + coef2 * B)</code> like this :</p>
  
  <pre><code>model = pd.ols(y=df['Y'],x=df[['A','B']],window_type='rolling',window=100)
  </code></pre>
  
  <p>and model.beta returns a DataFrame of the coef1 and coef2 ..</p>
  
  <p>in statsmodels I can do a polynomial regression, but there's no rolling window option:</p>
  
  <pre><code>poly_2 = smf.ols(formula='Y ~ 1 + A+ I(B** 2.0)', data=df).fit()
  </code></pre>
  
  <p>how could I 'mix' the 2 and have the rolling coefficients of this polynomial regression ?
  I didn't see in pandas a way to write patsy-style formulas, but maybe I searched badly.</p>
  
  <p>thanks for your help</p>