title: How to use statsmodels to fit data
body: <p>I have a dataset which I need to fit to a GEV distribution.  The data is one dimensional, and is stored in a numpy array.  Currently, I am using <code>scipy.stats.genextreme.fit(data)</code>, which works ok, but gives totally inaccurate results (obvious by plotting the pdf).  After some investigation it turns out that my data does not fit well in log space, which scipy uses in its MLE fitting algorithm, so I need to try something like GMM instead which is only available in statsmodels.  The problem is that I can't find anything which looks like scipy's <code>fit</code> function.  All the examples I've found seem to deal with far more complicated data than I have.  Also, <code>statsmodels</code> requires <code>endog</code> and <code>exog</code> parameters for eveything, and I have no idea what these are.</p>
  
  <p>This should be really simple, so I'm sure I'm missing something obvious.  Has anyone used statsmodels in this way, and if so, any pointers as to how to do it?</p>