nls()
nls()
.
nls.control(maxiter = 50, tolerance=.001, minscale=.001, trace = F)
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.
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.
Chambers, J. M., and Hastie, T. J. (eds) (1990). Statistical Models in S, Chapter 10, "Nonlinear Models", Pacific Grove, CA.
# take just one step, perhaps to check the algorithm by hand nls.control(maxiter=1, tolerance = .00001)