kelihood fits</h4>

A new option <tt>SumW2Error()</tt> has been added to <tt>RooAbsPdf::fitTo()</tt> that will
perform an improved error calculation for weighted unbinned likelihood fits. In their unmodified
form, an ML fit to a weighted dataset will correctly estimate the parameters, but the errors will
scale with the sum of the weights, rather than the number of the events in the dataset (i.e.
if you double all event weights, all parameter errors will go down with sqrt(2)). In chi-squared
fits event weigh