Control the Iterations in nls

nls.control {stats}

R Documentation

Allow the user to set some characteristics of the nls nonlinear least squares algorithm.

nls.control(maxiter = 50, tol = 1e-05, minFactor = 1/1024,
            printEval = FALSE, warnOnly = FALSE)

`maxiter`	A positive integer specifying the maximum number of iterations allowed.
`tol`	A positive numeric value specifying the tolerance level for the relative offset convergence criterion.
`minFactor`	A positive numeric value specifying the minimum step-size factor allowed on any step in the iteration. The increment is calculated with a Gauss-Newton algorithm and successively halved until the residual sum of squares has been decreased or until the step-size factor has been reduced below this limit.
`printEval`	a logical specifying whether the number of evaluations (steps in the gradient direction taken each iteration) is printed.
`warnOnly`	a logical specifying whether `nls()` should return instead of signalling an error in the case of termination before convergence. Termination before convergence happens upon completion of `maxiter` iterations, in the case of a singular gradient, and in the case that the step-size factor is reduced below `minFactor`.

A list with exactly five components:

with meanings as explained under ‘Arguments’.

Douglas Bates and Saikat DebRoy

Bates, D. M. and Watts, D. G. (1988), Nonlinear Regression Analysis and Its Applications, Wiley.

nls.control(minFactor = 1/2048)

[Package stats version 3.5.0 Index]