nlminb2: Constrained nonlinear minimization
In fPortfolio: Rmetrics - Portfolio Selection and Optimization

nlminb2

R Documentation

Constrained nonlinear minimization

Description

Solve constrained nonlinear minimization problem with nonlinear constraints using a penalty and barrier approach.

Usage

nlminb2(start, objective, eqFun = NULL, leqFun = NULL,  
    lower = -Inf, upper = Inf, gradient = NULL, hessian = NULL, 
    control = list(), env = .GlobalEnv)

Arguments

`start`	a numeric vector, initial values for the parameters to be optimized.
`objective`	function to be minimized. Must return a scalar value (possibly NA/Inf). The first argument to objective is the vector of parameters to be optimized, whose initial values are supplied through `start`. Further arguments (fixed during the course of the optimization) to objective may be specified as well. see `env`.
`eqFun`	a list of functions describing equal constraints.
`leqFun`	a list of functions describing less equal constraints.
`lower, upper`	two vectors of lower and upper bounds, replicated to be as long as `start`. If unspecified, all parameters are assumed to be unconstrained.
`gradient`	an optional function that takes the same arguments as `objective` and evaluates the gradient of `objective` at its first argument. Must return a vector as long as `start`.
`hessian`	an optional function that takes the same arguments as `objective` and evaluates the hessian of `objective` at its first argument. Must return a square matrix of order `length(start)`. Only the lower triangle is used.
`control`	a list of control parameters. See below for details.
`env`	the environment in which objective, constraint, control functions are evaluated.

Value

A list with following elements:

`par`	a numeric vector, the best set of parameters found.
`objective`	a numeric value, the value of `objective` corresponding to `par`.
`convergence`	an integer code, 0 indicates successful convergence.
`message`	a character string giving any additional information returned by the optimizer, or NULL. For details, see PORT documentation.
`iterations`	am integer value, the number of iterations performed.
`evaluations`	an integer value, the number of objective function and gradient function evaluations.

Author(s)

For the R port of nlminb Douglas Bates and Deepayan Sarkar, for the R/Rmetrics port of nlminb2 Diethelm Wuertz, for the PORT library netlib.bell-labs.com.

References

Paul A. Jensen & Jonathan F. Bard, Operations Research Models and Methods, 2001 Appendix A, Algorithms for Constrained Optimization, https://www.me.utexas.edu/~jensen/ORMM/supplements/index.html.

PORT Library, https://netlib.org/port/.

fPortfolio documentation built on April 25, 2023, 9:11 a.m.