# nlminb2: Nonlinear programming with nonlinear constraints. In ROI: R Optimization Infrastructure

## Description

This function was contributed by Diethelm Wuertz.

## Usage

 ```1 2``` ```nlminb2(start, objective, eqFun = NULL, leqFun = NULL, lower = -Inf, upper = Inf, gradient = NULL, hessian = NULL, control = list()) ```

## Arguments

 `start` numeric vector of start values. `objective` the function to be minimized f(x). `eqFun` functions specifying equal constraints of the form h_i(x) = 0. Default: `NULL` (no equal constraints). `leqFun` functions specifying less equal constraints of the form g_i(x) <= 0. Default: `NULL` (no less equal constraints). `lower` a numeric representing lower variable bounds. Repeated as needed. Default: `-Inf`. `upper` a numeric representing upper variable bounds. Repeated as needed. Default: `Inf`. `gradient` gradient of f(x). Default: `NULL` (no gradiant information). `hessian` hessian of f(x). Default: `NULL` (no hessian provided). `control` a list of control parameters. See `nlminb()` for details. The parameter `"scale"` is set here in contrast to `nlminb()` .

list()

Diethelm Wuertz

## Examples

 ```1 2 3 4 5 6 7``` ```## Equal constraint function eval_g0_eq <- function( x, params = c(1,1,-1)) { return( params[1]*x^2 + params[2]*x + params[3] ) } eval_f0 <- function( x, ... ) { return( 1 ) } ```

ROI documentation built on Jan. 27, 2018, 1:04 a.m.