code: def apply_karhunen_loeve_scaling(self):
          
          cnames = copy.deepcopy(self.jco.col_names)
          self.__jco *= self.fehalf
          self.__jco.col_names = cnames
          self.__parcov = self.parcov.identity
docs: apply karhuene-loeve scaling to the jacobian matrix.
  
          Note
          ----
          This scaling is not necessary for analyses using Schur's
          complement, but can be very important for error variance
          analyses.  This operation effectively transfers prior knowledge
          specified in the parcov to the jacobian and reset parcov to the
          identity matrix.