SIXLIN

       Compute linear regression coefficients by six different methods.

       Adapted from the FORTRAN program (Rev. 1.1)  supplied by Isobe,
       Feigelson, Akritas, and Babu Ap. J. Vol. 364, p. 104 (1990).
       Suggested when there is no understanding about the nature of the
       scatter about a linear relation, and NOT when the errors in the
       variable are calculable.

       SIXLIN, xx, yy, a, siga, b, sigb

       XX - vector of X values
       YY - vector of Y values, same number of elements as XX

       A - Vector of 6 Y intercept coefficients
       SIGA - Vector of standard deviations of 6 Y intercepts
       B - Vector of 6 slope coefficients
       SIGB - Vector of standard deviations of slope coefficients
       The output variables are computed using linear regression for each of
       the following 6 cases:
               (0) Ordinary Least Squares (OLS) Y vs. X
               (1) Ordinary Least Squares  X vs. Y
               (2) Ordinary Least Squares Bisector
               (3) Orthogonal Reduced Major Axis
               (4) Reduced Major-Axis
               (5) Mean ordinary Least Squares

       Isobe et al. make the following recommendations
       (1) If the different linear regression methods yield similar results
               then quoting OLS(Y|X) is probably the most familiar.
       (2) If the linear relation is to be used to predict Y vs. X then
               OLS(Y|X) should be used.
       (3) If the goal is to determine the functional relationship between
               X and Y then the OLS bisector is recommended.

       Written   Wayne Landsman          February, 1991
       Corrected sigma calculations      February, 1992
       Converted to IDL V5.0   W. Landsman   September 1997

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