

   OOnnee DDiimmeennssiioonnaall OOppttiimmiizzaattiioonn

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

   AArrgguummeennttss::

          f: the function to be optimized. The function is
             either minimized or maximized over its first argu-
             ment 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'.

   DDeessccrriippttiioonn::

        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'.

   VVaalluuee::

        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.

   RReeffeerreenncceess::

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

   SSeeee AAllssoo::

        `nlm', `uniroot'.

   EExxaammpplleess::

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

