R: New Unconstrained Optimization with quadratic Approximation

newuoa {nloptr} | R Documentation

## New Unconstrained Optimization with quadratic Approximation

### Description

NEWUOA solves quadratic subproblems in a spherical trust regionvia a truncated conjugate-gradient algorithm. For bound-constrained problems, BOBYQA shold be used instead, as Powell developed it as an enhancement thereof for bound constraints.

### Usage

    newuoa(x0, fn, nl.info = FALSE, control = list(), ...)

### Arguments

`x0` | starting point for searching the optimum.
`fn` | objective function that is to be minimized.
`nl.info` | logical; shall the original NLopt info been shown.
`control` | list of options, see `nl.opts` for help.
`...` | additional arguments passed to the function.

### Details

This is an algorithm derived from the NEWUOA Fortran subroutine of Powell, converted to C and modified for the NLOPT stopping criteria.

### Value

List with components:

`par` | the optimal solution found so far.
`value` | the function value corresponding to `par`.
`iter` | number of (outer) iterations, see `maxeval`.
`convergence` | integer code indicating successful completion (> 0) or a possible error number (< 0).
`message` | character string produced by NLopt and giving additional information.

### Note

NEWUOA may be largely superseded by BOBYQA.

### Author(s)

Hans W. Borchers

### References

M. J. D. Powell. “The BOBYQA algorithm for bound constrained optimization without derivatives,” Department of Applied Mathematics and Theoretical Physics, Cambridge England, technical reportNA2009/06 (2009).

### See Also

`bobyqa`, `cobyla`

### Examples

    fr <- function(x) {   ## Rosenbrock Banana function
        100 * (x[2] - x[1]^2)^2 + (1 - x[1])^2
    }
    (S <- newuoa(c(1, 2), fr))

[Package nloptr version 1.2.2.2 Index]