docs: def _getScalesRand(self):
          """
          Internal function for parameter initialization
          Return a vector of random scales
          """
          if self.P>1:
              scales = []
              for term_i in range(self.n_randEffs):
                  _scales = sp.randn(self.diag[term_i].shape[0])
                  if self.jitter[term_i]>0:
                      _scales = sp.concatenate((_scales,sp.array([sp.sqrt(self.jitter[term_i])])))
                  scales.append(_scales)
              scales = sp.concatenate(scales)
          else:
              scales=sp.randn(self.vd.getNumberScales())
          return scales