I'm an experimental physicist who is using S-Plus (4.5 on W98
machine). No doubt my statistical sophistication pales in comparison
with 99% of the readers of this group. In my work I'm usually faced
with y values, x values, errors (or sigmas) on y, and a nonlinear
function with unknown parameters that is supposed to describe the
relationship between y and x. There's A LOT OF discussion of fitting
in the S-Plus documentation and 3rd party books, but none of it speaks
exactly to me. From what I've read, I'm inclined to try the
following:
nls( y/sy ~ f(x,a,b,c)/sy , data = x )
Can you experts tell me if this is the way to perform a weighted
nonlinear fit using S-Plus?
I've been reading up on the deriv() function which seems to be a neat
way to generate the information needed by nls. It returns an
"expression" while nls takes a "formula". I presume there is a simple
way to turn an expression into a formula. I haven't found a full
example yet that shows how this works. I understand the "gradient"
attribute concept.
Thanks in advance,
Scott Dewey
National Institute of Standards and Technology
Bld. 235, Rm. A159, Gaithersburg, MD 20899
Ph: (301) 975-4843 Fx: (301) 926-1604
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