Control the Iteration in nls()

DESCRIPTION:

Allows the user to set values affecting nls().

USAGE:

nls.control(maxiter = 50, tolerance=.001, minscale=.001, trace = F) 

OPTIONAL ARGUMENTS:

maxiter
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.

SEE ALSO:

.

EXAMPLES:

# take just one step, perhaps to check the algorithm by hand 
nls.control(maxiter=1, tolerance = .00001)