def logL(self, ML=False):
        #I don't know what the difference between REML and ML is here.
        logL = 0.

        for unit in self.units:
            logL += unit.logL(a=self.a, ML=ML)
        if not ML:
            logL += np.log(L.det(self.Sinv)) / 2
        return logL
Return log-likelihood, REML by default.
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/sandbox/panel/mixed.py/OneWayMixed.logL