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;; define a function to compute the Box-Cox transformation
(defun bc (x c p)
(let* ((x (- x c))
(bcx (if (< (abs p) .0001)
(log x)
(/ (^ x p) p)))
(min (min bcx))
(max (max bcx)))
(/ (- bcx min) (- max min))))
;; get a sorted sample from a shi-squared distribution
(def x (sort-data (chisq-rand 30 4)))
;; compute the normal quantiles of the expected uniform order statistics
(def r (normal-quant (/ (iseq 1 30) 31)))
;; construct an initial plot without transformation
(def myplot (plot-points r (bc x 0 1)))
;;;
;;; First approach: compute as needed
;;;
;; construct a dialog for scrolling through powers and recomputing the
;; plot
#|
(interval-slider-dialog (list -1 2)
:points 20
:action #'(lambda (p)
(send myplot :clear nil)
(send myplot
:add-points r (bc x 0 p))))
|#
;;;
;;; Second aproach: precompute
;;;
;; construct a list of powers
(def powers (rseq -1 2 16))
;; compute transformed data for each power
(def xlist (mapcar #'(lambda (p) (bc x 0 p)) powers))
;; construct a dialog for scrolling through the list of data sets
;; and redrawing the plot
(sequence-slider-dialog xlist
:display powers
:action #'(lambda (x)
(send myplot :clear nil)
(send myplot :add-points r x)))
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