docs: def model_at_upper_sigma_limit(self, sigma_limit):
          """Setup 1D vectors of the upper and lower limits of the multinest nlo.
  
          These are generated at an input limfrac, which gives the percentage of 1d posterior weighted samples within \
          each parameter estimate
  
          Parameters
          -----------
          sigma_limit : float
              The sigma limit within which the PDF is used to estimate errors (e.g. sigma_limit = 1.0 uses 0.6826 of the \
              PDF).
          """
          return list(map(lambda param: param[1], self.model_at_sigma_limit(sigma_limit)))