anchor.diff:  		      (* y (horner y 0.2548296d0 -0.28449672d0 1.4214138d0
   				      -1.4531521d0 1.0614054d0))))
   		    'single-float))))
  -#+testing
  -(defun erf-int (z dx)
  -  (loop for x from 0.0d0 to z by dx
  -	sum (* dx (gaussian x)) into sum
  -	finally (return sum)))
  -
  -#+testing
  -(defun erf-series (x)
  -  "Series erf function 7.1.5 of Abramowitz and Segun."
  -  (setq x (float x))
  -  (loop for n from 0 by 1 
  -	for term = x then (/ (* -1.0d0 term (expt x 2)) n)
  -	while (> (abs term) (* 1.e-16 sum))
  -	sum (/ term (+ 1.0 n n)) into sum
  -	finally (return (/ (* 2.0 sum) #.(sqrt pi)))))
  -
  -#+testing
  -(defun make-it (N)
  -  (let ((data ())
  -	(last (uniform)))
  -    (dotimes (i N)
  -      (push (list last (setq last (uniform))) data))
  -    (make-instance 'graph::graph-data :data (nreverse data) :data-symbol :point)))
   
   ;;;
   ;;; Numerical Recipes in LISP
  
positive.code: 
  (defun random-seed ()
    "Return a random seed."
    #-system-random (get-internal-real-time)	; integer
    #+system-random (make-random-state))		; structure
  
  #-system-random
  (eval-when (compile load eval)
    (when (>= most-positive-fixnum *uniform-m*)
      (pushnew ':fast-random-numbers *features*)))
  
  #-fast-random-numbers
  (defun uniform-basic (previous-fixnum)
    "Returns a random fixnum between 1 and (1- *uniform-m*)."
    #||
  
negative.code:    If low-num and/or high-num are fixnums, a fixnum is returned."
    (if (= low-num high-num)
        low-num
      (+ low-num (random (- high-num low-num)))  ))
  
  (defun gaussian-random-1 ()
    "Returns a gaussian random variable with mean 0.0 and standard deviation 1.0.
     Good tails."
    (* (sqrt (* -2.0 (log (random 1.0))))
       (sin (* #.(* 2.0 (coerce pi 'single-float)) (random 1.0)))))
  
  