maximum number of iterations during fitting. Default 50.
tolerance:
tolerance for the relative offset convergence criterion in the algorithm.
Default 0.001.
Note that the convergence test used in nls() is strictly relative.
Therefore if the solution to a problem turned out to be a perfect
fit (unlikely except in artificial examples), convergence is not
guaranteed to be recognized by the algorithm.
minscale:
minimum factor by which to shrink the default step size in an attempt
to decrease the sum of squares. Default 0.001.
VALUE:
a list containing components for each of the possible arguments,
either the value supplied by the user or the default.
DETAILS:
The functions nls() and ms() use several values to control
the characteristics of their optimization algorithms. The control
argument is used to specify a list of control values to these
functions.
REFERENCES:
Chambers, J. M., and Hastie, T. J. (eds) (1990).
Statistical Models in S,
Chapter 10, "Nonlinear Models", Pacific Grove, CA.