Observations 
              | 
          nobs  = The number of
            lines fitted or the number of experimental points for a
            contour fit 
           | 
        
        
          Parameters 
              | 
          npar = The number of parameters
            floated 
           | 
        
        
          Initial Average Error 
              | 
          This is [Σ[(obsi-calci)/wi]2/(nobs-npar)]½
            with the calculated values, calci, obtained using
            the parameters at their initial values. wi
            are the estimated (relative) standard deviations of the
            observations. 
           | 
        
        
          | Predicted New Error | 
          This is [Σ[(obsi-calci)/wi]2/(nobs-npar)]½
            with the calculated values, calci, obtained from
            the non-linear least squares fit. They are typically close
            to the values that would be obtained from the new
            parameters, but are only exact if the calculated values are
            linear (or nearly linear) in the parameters. This is should
            be the case near to convergence, but often not when starting
            the fitting process. Fit again to find the true new error. 
           | 
        
        
          Old 
              | 
          The parameter value at the
            start of the fit. 
           | 
        
        
          New 
              | 
          The parameter value after the
            fit cycle. 
           | 
        
        
          Std Dev 
              | 
          The estimated standard
            deviation of the parameter, based on the quality of the fit. 
           | 
        
        
          Change/Std 
              | 
          (New-Old)/Std Dev - the relative change in
            the parameter. 
           | 
        
        
          Sens 
              | 
          Watson's sensitivity
            parameter (J. K. G. Watson, J. Mol. Spectrosc. 66, 500 (1977)) for the
            parameter. This is the change in the parameter that would
            make the average error of the fit increase by a factor of
            0.1/npar,
            and provides a useful guide as to how many figures should be
            quoted for the parameter to ensure that the calculation can
            be reproduced. Where parameter correlation is high, this can
            be many more figures than suggested by the standard
            deviation of the parameter. See also R. J. Le Roy, J. Mol.
            Spectrosc. 191, 223 (1998) for discussion of this
            issue, and alternative approaches. 
           | 
        
        
          Deriv Diff 
              | 
          This column and the next are only shown if
            "Check Derivatives" is selected. This prompts for a
            multiple, c, and then for each parameter calculates
            a maximum difference in derivatives using the default
            increment, and the increment multiplied by c.
            Formally the derivative of a calculated value, y,
            with respect to a parameter, p, is worked out using: 
            dy/dp = (y(p+i)-y(p))/i 
               
            where i is the increment for the parameter. The
            value displayed here is the largest difference between
            derivatives calculated with increments i and i×c,
            looking over all observations. It is divided by the largest
            derivative for that parameter, again looking at all
            observations. 
           | 
        
        
          Obs# 
              | 
          The observation number of the largest
            derivative difference shown in the previous column. 
           | 
        
        
          Summary 
              | 
          The new parameter, with the
            one standard deviation in units of the last figure in
            brackets. The sensitivity is used to determine how many
            figures are displayed for the standard deviation. 
           | 
        
        
          | Correlation Matrix | 
          The correlation between the
            parameters. 
           |