GRADLS(3M)

NAME
gradls

DESCRIPTION
subroutine gradls.f source
  Bevington, pages 220-222. purpose
  make gradient-search least-squares fit to data with a
    specified function which is not linear in coefficients usage
  call gradls (x, y, sigmay, npts, nterms, mode, a, deltaa,
    yfit, chisqr) description of parameters
  x - array of data points for independent variable
  y - array of data points for dependent variable
  sigmay - array of standard deviations for y data points
  npts - number of pairs of data points
  nterms - number of parameters
  mode - determines method of weighting least-squares fit
           +1 (instrumental) weight(i) = 1./sigmay(i)**2
            0 (no weighting) weight(i) = 1.
           -1 (statistical) weight(i) = 1./y(i)
  a - array of parameters
  deltaa - array of increments for parameters a
  yfit - array of calculated values of y
  chisqr - reduced chi square for fit subroutines and function subprograms required
  functn (x, i, a)
    evaluates the fitting function for the ith term
  fchisq (y, sigmay, npts, nfree, mode, yfit)
    evaluates reduced chi squared for fit to data comments
  valid for nterms up to 10