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+@noindent
+
+The Golden Section Search
+@footnote{David Kahaner, Cleve Moler, and Stephen Nash
+@cite{Numerical Methods and Software}
+Prentice-Hall, 1989, ISBN 0-13-627258-4}
+algorithm finds minima of functions which
+are expensive to compute or for which derivatives are not available.
+Although optimum for the general case, convergence is slow,
+requiring nearly 100 iterations for the example (x^3-2x-5).
+
+@noindent
+
+If the derivative is available, Newton-Raphson is probably a better
+choice.  If the function is inexpensive to compute, consider
+approximating the derivative.
+
+
+@defun golden-section-search f x0 x1 prec
+
+
+@var{x_0} are @var{x_1} real numbers.  The (single argument)
+procedure @var{f} is unimodal over the open interval (@var{x_0},
+@var{x_1}).  That is, there is exactly one point in the interval for
+which the derivative of @var{f} is zero.
+
+@code{golden-section-search} returns a pair (@var{x} . @var{f}(@var{x})) where @var{f}(@var{x})
+is the minimum.  The @var{prec} parameter is the stop criterion.  If
+@var{prec} is a positive number, then the iteration continues until
+@var{x} is within @var{prec} from the true value.  If @var{prec} is
+a negative integer, then the procedure will iterate @var{-prec}
+times or until convergence.  If @var{prec} is a procedure of seven
+arguments, @var{x0}, @var{x1}, @var{a}, @var{b}, @var{fa}, @var{fb},
+and @var{count}, then the iterations will stop when the procedure
+returns @code{#t}.
+
+Analytically, the minimum of x^3-2x-5 is 0.816497.
+@example
+(define func (lambda (x) (+ (* x (+ (* x x) -2)) -5)))
+(golden-section-search func 0 1 (/ 10000))
+      ==> (816.4883855245578e-3 . -6.0886621077391165)
+(golden-section-search func 0 1 -5)
+      ==> (819.6601125010515e-3 . -6.088637561916407)
+(golden-section-search func 0 1
+                       (lambda (a b c d e f g ) (= g 500)))
+      ==> (816.4965933140557e-3 . -6.088662107903635)
+@end example
+@end defun