code: def _init_params_default(self):
          
          # if there are some nan -> mean impute
          Yimp = self.Y.copy()
          Inan = sp.isnan(Yimp)
          Yimp[Inan] = Yimp[~Inan].mean()
          if self.P==1:   C = sp.array([[Yimp.var()]])
          else:           C = sp.cov(Yimp.T)
          C /= float(self.n_randEffs)
          for ti in range(self.n_randEffs):
              self.getTraitCovarFun(ti).setCovariance(C)
docs: Internal method for default parameter initialization