R: One Dimensional Optimization

optimize {base} | R Documentation

## One Dimensional Optimization

### Description

The function `optimize` searches the interval from `lower` to `upper` for a minimum or maximum of the function `f` with respect to its first argument.

It uses Fortran code (from Netlib) based on algorithms given in the reference.

`optimise` is an alias for `optimize`.

### Usage

    optimize(f = , interval = , lower = min(interval),
            upper = max(interval), maximum = FALSE,
            tol = .Machine$double.eps^0.25, ...)
    optimise(f = , interval = , lower = min(interval),
            upper = max(interval), maximum = FALSE,
            tol = .Machine$double.eps^0.25, ...)

### Arguments

`f` | the function to be optimized. The function is either minimized or maximized over its first argument depending on the value of `maximum`.
`interval` | a vector containing the end-points of the interval to be searched for the minimum.
`lower` | the lower end point of the interval to be searched.
`upper` | the upper end point of the interval to be searched.
`maximum` | logical. Should we maximize or minimize (the default)?
`tol` | the desired accuracy.
`...` | additional arguments to `f`.

### Value

A list with components `minimum` (or `maximum`) and `objective` which give the location of the minimum (or maximum) and the value of the function at that point.

### References

Brent, R. (1973) Algorithms for Minimization without Derivatives. Englewood Cliffs N.J.: Prentice-Hall.

### See Also

`nlm`, `uniroot`.

### Examples

    f <- function (x,a) (x-a)^2
    xmin <- optimize(f, c(0, 1), tol = 0.0001, a = 1/3)
    xmin

[Package Contents]