## One Dimensional Optimization

## Usage

    optimise(.........)
    optimize(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.
`tol` | the desired accuracy.
`...` | additional arguments to `f`.

## 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`.

## 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

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