def nloglikeobs(self, params):

        errorsest = self.geterrors(params[:-2])
        #sigma2 = np.maximum(params[-1]**2, 1e-6)  #do I need this
        #axis = 0
        #nobs = len(errorsest)

        df = params[-2]
        scale = np.abs(params[-1])
        llike  = - stats.t._logpdf(errorsest/scale, df) + np_log(scale)
        return llike

    #TODO rename fit_mle -> fit, fit -> fit_ls
Convert to formal string, for repr().
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/miscmodels/tmodel.py/TArma.nloglikeobs--crossover with--dataset/ETHPy150Open azoft-dev-team/imagrium/env/Lib/datetime.py/datetime.__repr__