minpack.lm: nls.lm.control – R documentation

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nls.lm.control

Control various aspects of the Levenberg-Marquardt algorithm

Description

Allow the user to set some characteristics Levenberg-Marquardt nonlinear least squares algorithm implemented in nls.lm.

Usage

nls.lm.control(ftol = sqrt(.Machine$double.eps),
ptol = sqrt(.Machine$double.eps), gtol = 0, diag = list(), epsfcn = 0,
factor = 100, maxfev = integer(), maxiter = 50, nprint = 0)

Arguments

`ftol`	non-negative numeric. Termination occurs when both the actual and predicted relative reductions in the sum of squares are at most `ftol`. Therefore, `ftol` measures the relative error desired in the sum of squares.
`ptol`	non-negative numeric. Termination occurs when the relative error between two consecutive iterates is at most `ptol`. Therefore, `ptol` measures the relative error desired in the approximate solution.
`gtol`	non-negative numeric. Termination occurs when the cosine of the angle between result of `fn` evaluation fvec and any column of the Jacobian is at most `gtol` in absolute value. Therefore, `gtol` measures the orthogonality desired between the function vector and the columns of the Jacobian.
`diag`	a list or numeric vector containing positive entries that serve as multiplicative scale factors for the parameters. Length of `diag` should be equal to that of `par`. If not, user-provided `diag` is ignored and `diag` is internally set.
`epsfcn`	(used if `jac` is not provided) is a numeric used in determining a suitable step for the forward-difference approximation. This approximation assumes that the relative errors in the functions are of the order of `epsfcn`. If `epsfcn` is less than the machine precision, it is assumed that the relative errors in the functions are of the order of the machine precision.
`factor`	positive numeric, used in determining the initial step bound. This bound is set to the product of `factor` and the \|\code{diag}\code{par}\|* if nonzero, or else to `factor` itself. In most cases `factor` should lie in the interval (0.1,100). 100 is a generally recommended value.
`maxfev`	integer; termination occurs when the number of calls to `fn` has reached `maxfev`. Note that `nls.lm` sets the value of `maxfev` to `100*(length(par) + 1)` if `maxfev = integer()`, where `par` is the list or vector of parameters to be optimized.
`maxiter`	positive integer. Termination occurs when the number of iterations reaches `maxiter`.
`nprint`	is an integer; set `nprint` to be positive to enable printing of iterates

Value

A list with exactly nine components:

`ftol`
`ptol`
`gtol`
`diag`
`epsfcn`
`factor`
`maxfev`
`nprint`

with meanings as explained under ‘Arguments’.

References

J.J. Moré, "The Levenberg-Marquardt algorithm: implementation and theory," in Lecture Notes in Mathematics 630: Numerical Analysis, G.A. Watson (Ed.), Springer-Verlag: Berlin, 1978, pp. 105-116.

Examples

nls.lm.control(maxiter = 4)

minpack.lm

R Interface to the Levenberg-Marquardt Nonlinear Least-Squares Algorithm Found in MINPACK, Plus Support for Bounds

v1.2-1

GPL-3

Authors

Timur V. Elzhov, Katharine M. Mullen, Andrej-Nikolai Spiess, Ben Bolker

Initial release