Yes, you should be able to do start={"params_fe": r.params_fe, "cov_re":
r.cov_re, "sig2": r.sig2}, where r is a results object from a previous run.


On Sat, Mar 22, 2014 at 7:05 PM, Josef Perktold <notifications@github.com>wrote:

> In statsmodels/regression/lme.py:
>
> > +                sl /= 2
> > +
> > +            if not success:
> > +                break
> > +
> > +        return params, np.max(np.abs(gro)) < gtol
> > +
> > +    def fit(self, start=None, reml=True, num_sd=2,
> > +            num_em=0, do_cg=True, pen=0., gtol=1e-4, use_L=True,
> > +            free=None, full_output=False):
> > +        """
> > +        Fit a linear mixed model to the data.
> > +
> > +        Parameters
> > +        ----------
> > +        start: dict
>
> Is there an easy way to continue from a previous estimate?
> How do we set start if we already called fit once, and we want to refine
> or try a different fit?
>
> --
> Reply to this email directly or view it on GitHub<https://github.com/statsmodels/statsmodels/pull/1398/files#r10861800>
> .
>