R: Control the Iterations in nls

nls.control {stats} | R Documentation

## Control the Iterations in nls

### Description

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

### Usage

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

### Arguments

`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`.

### Value

A `list` with exactly five components:

`maxiter` |
`tol` |
`minFactor` |
`printEval` |
`warnOnly` |

with meanings as explained under ‘Arguments’.

### Author(s)

Douglas Bates and Saikat DebRoy

### References

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

### See Also

`nls`

### Examples

    nls.control(minFactor = 1/2048)

[Package stats version 4.0.5 Index]