BF: use proper scale into HuberScale estimator instead of stand_mad.

In the IRLS algorithm, Huber's scale update is:

"sigma^{n+1} = 1/n*a * sum(\chi(r_i/s)) * s ** 2,"

where "s = sigma^{n}".

Actual statsmodels' master branch uses "s = mad(r)" by default instead and there is no possibility to change this. In the literature, mad(r) is sometimes used directly to perform the scale update (I guess for code simplification purpose), but I cannot find any reason why we would use mad(r) in combination with an HuberScale estimator.

For backward compatibility reasons, MAD stay the default init scale estimator in HuberScale iterations when None is provided.