R version 2.8.1 (2008-12-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> y <- c(241.66,251.25,230.26,240.91,211.20,188.19,177.01,167.85,174.03,170.09,203.42,254.97,342.84,386.29,440.51,433.58,408.13,370.32,355.51,332.62,314.62,301.73,306.31,282.98,266.48,249.97,259.87,246.24,238.36,238.04,224.19,214.71,203.11,221.00,211.73,209.39,217.48,242.19,244.64,232.07,235.80,230.37,209.82,206.41,209.60,192.24,186.17,193.41,202.36,203.00,190.64,185.43,171.58,179.57,180.42,162.10,157.95,146.66,154.43,163.38,150.92,151.98,144.74,140.37,143.36,135.79,134.73,126.42,124.72,117.90,114.07,112.26,105.44,110.77,107.68,105.76,102.03,100.22,111.62,118.11,111.72,103.42,97.13,103.10,104.91,100.22,98.52,95.32,96.92,96.60,92.55,82.75,80.84,79.13,79.77,85.10,96.39,97.56,96.39,101.18,103.52,100.11,99.26,104.48,101.29,100.33,115.24,113.64,115.35,108.42,105.65,108.64,104.80,95.43,104.48,103.84,100.01)
> x <- c(83.33,83.33,78.33,77.50,76.67,74.17,72.50,72.50,75.83,71.67,74.17,78.33,85.00,83.33,81.67,83.33,85.00,86.67,90.00,90.00,87.50,89.17,85.83,91.67,90.83,90.83,91.67,93.33,94.17,94.17,91.67,93.33,91.67,85.83,93.33,94.17,90.83,90.83,90.83,90.83,87.50,89.17,88.33,90.83,91.67,88.33,85.00,85.83,80.83,84.17,83.33,83.33,83.33,88.33,90.83,90.00,87.50,87.50,86.67,87.50,90.83,90.83,89.17,92.50,87.50,89.17,90.00,91.67,90.00,87.50,87.50,80.00,88.33,83.33,81.67,84.17,85.00,83.33,77.50,81.67,85.00,85.83,89.17,90.00,90.00,90.00,91.67,92.50,93.33,92.50,94.17,93.33,91.67,85.83,77.50,80.83,89.17,92.50,95.83,95.83,95.00,95.00,98.33,99.17,103.33,105.00,104.17,104.17,100.83,105.83,103.33,105.00,103.33,102.50,103.33,101.67,100.00)
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> n <- length(x)
> c <- array(NA,dim=c(401))
> l <- array(NA,dim=c(401))
> mx <- 0
> mxli <- -999
> for (i in 1:401)
+ {
+ l[i] <- (i-201)/100
+ if (l[i] != 0)
+ {
+ x1 <- (x^l[i] - 1) / l[i]
+ } else {
+ x1 <- log(x)
+ }
+ c[i] <- cor(x1,y)
+ if (mx < abs(c[i]))
+ {
+ mx <- abs(c[i])
+ mxli <- l[i]
+ }
+ }
> c
  [1] -0.2521351 -0.2522944 -0.2524535 -0.2526126 -0.2527716 -0.2529306
  [7] -0.2530894 -0.2532482 -0.2534069 -0.2535655 -0.2537240 -0.2538825
 [13] -0.2540409 -0.2541992 -0.2543574 -0.2545155 -0.2546735 -0.2548315
 [19] -0.2549894 -0.2551472 -0.2553049 -0.2554625 -0.2556200 -0.2557775
 [25] -0.2559349 -0.2560922 -0.2562494 -0.2564065 -0.2565635 -0.2567205
 [31] -0.2568773 -0.2570341 -0.2571908 -0.2573474 -0.2575039 -0.2576603
 [37] -0.2578166 -0.2579728 -0.2581290 -0.2582850 -0.2584410 -0.2585969
 [43] -0.2587527 -0.2589084 -0.2590640 -0.2592195 -0.2593749 -0.2595302
 [49] -0.2596855 -0.2598406 -0.2599956 -0.2601506 -0.2603054 -0.2604602
 [55] -0.2606149 -0.2607695 -0.2609239 -0.2610783 -0.2612326 -0.2613868
 [61] -0.2615409 -0.2616949 -0.2618488 -0.2620026 -0.2621563 -0.2623099
 [67] -0.2624634 -0.2626168 -0.2627701 -0.2629233 -0.2630764 -0.2632295
 [73] -0.2633824 -0.2635352 -0.2636879 -0.2638405 -0.2639930 -0.2641454
 [79] -0.2642977 -0.2644499 -0.2646020 -0.2647540 -0.2649059 -0.2650577
 [85] -0.2652093 -0.2653609 -0.2655124 -0.2656637 -0.2658150 -0.2659662
 [91] -0.2661172 -0.2662682 -0.2664190 -0.2665697 -0.2667203 -0.2668709
 [97] -0.2670213 -0.2671716 -0.2673218 -0.2674718 -0.2676218 -0.2677717
[103] -0.2679214 -0.2680711 -0.2682206 -0.2683700 -0.2685193 -0.2686685
[109] -0.2688176 -0.2689666 -0.2691155 -0.2692642 -0.2694129 -0.2695614
[115] -0.2697098 -0.2698581 -0.2700063 -0.2701544 -0.2703024 -0.2704502
[121] -0.2705979 -0.2707456 -0.2708931 -0.2710404 -0.2711877 -0.2713349
[127] -0.2714819 -0.2716288 -0.2717756 -0.2719223 -0.2720689 -0.2722153
[133] -0.2723617 -0.2725079 -0.2726540 -0.2728000 -0.2729458 -0.2730915
[139] -0.2732372 -0.2733827 -0.2735280 -0.2736733 -0.2738184 -0.2739634
[145] -0.2741083 -0.2742531 -0.2743978 -0.2745423 -0.2746867 -0.2748310
[151] -0.2749751 -0.2751191 -0.2752631 -0.2754068 -0.2755505 -0.2756940
[157] -0.2758375 -0.2759807 -0.2761239 -0.2762669 -0.2764098 -0.2765526
[163] -0.2766953 -0.2768378 -0.2769802 -0.2771225 -0.2772646 -0.2774067
[169] -0.2775486 -0.2776903 -0.2778320 -0.2779735 -0.2781148 -0.2782561
[175] -0.2783972 -0.2785382 -0.2786791 -0.2788198 -0.2789604 -0.2791009
[181] -0.2792412 -0.2793814 -0.2795215 -0.2796614 -0.2798012 -0.2799409
[187] -0.2800805 -0.2802199 -0.2803591 -0.2804983 -0.2806373 -0.2807762
[193] -0.2809149 -0.2810535 -0.2811920 -0.2813304 -0.2814686 -0.2816066
[199] -0.2817446 -0.2818824 -0.2820200 -0.2821576 -0.2822949 -0.2824322
[205] -0.2825693 -0.2827063 -0.2828431 -0.2829798 -0.2831164 -0.2832528
[211] -0.2833891 -0.2835253 -0.2836613 -0.2837972 -0.2839329 -0.2840685
[217] -0.2842039 -0.2843393 -0.2844744 -0.2846095 -0.2847444 -0.2848791
[223] -0.2850137 -0.2851482 -0.2852825 -0.2854167 -0.2855507 -0.2856846
[229] -0.2858184 -0.2859520 -0.2860855 -0.2862188 -0.2863520 -0.2864851
[235] -0.2866180 -0.2867507 -0.2868833 -0.2870158 -0.2871481 -0.2872803
[241] -0.2874123 -0.2875442 -0.2876760 -0.2878076 -0.2879390 -0.2880703
[247] -0.2882015 -0.2883325 -0.2884633 -0.2885941 -0.2887246 -0.2888551
[253] -0.2889853 -0.2891155 -0.2892454 -0.2893753 -0.2895050 -0.2896345
[259] -0.2897639 -0.2898931 -0.2900222 -0.2901511 -0.2902799 -0.2904086
[265] -0.2905371 -0.2906654 -0.2907936 -0.2909216 -0.2910495 -0.2911773
[271] -0.2913048 -0.2914323 -0.2915596 -0.2916867 -0.2918137 -0.2919405
[277] -0.2920672 -0.2921937 -0.2923201 -0.2924463 -0.2925724 -0.2926983
[283] -0.2928240 -0.2929496 -0.2930751 -0.2932004 -0.2933255 -0.2934505
[289] -0.2935754 -0.2937000 -0.2938246 -0.2939489 -0.2940732 -0.2941972
[295] -0.2943211 -0.2944449 -0.2945685 -0.2946919 -0.2948152 -0.2949383
[301] -0.2950613 -0.2951841 -0.2953067 -0.2954292 -0.2955516 -0.2956738
[307] -0.2957958 -0.2959177 -0.2960394 -0.2961609 -0.2962823 -0.2964036
[313] -0.2965247 -0.2966456 -0.2967663 -0.2968869 -0.2970074 -0.2971277
[319] -0.2972478 -0.2973678 -0.2974876 -0.2976072 -0.2977267 -0.2978460
[325] -0.2979652 -0.2980842 -0.2982031 -0.2983218 -0.2984403 -0.2985587
[331] -0.2986769 -0.2987949 -0.2989128 -0.2990305 -0.2991481 -0.2992655
[337] -0.2993827 -0.2994998 -0.2996167 -0.2997334 -0.2998500 -0.2999664
[343] -0.3000827 -0.3001988 -0.3003147 -0.3004305 -0.3005461 -0.3006616
[349] -0.3007768 -0.3008920 -0.3010069 -0.3011217 -0.3012363 -0.3013508
[355] -0.3014651 -0.3015792 -0.3016932 -0.3018070 -0.3019207 -0.3020341
[361] -0.3021475 -0.3022606 -0.3023736 -0.3024864 -0.3025990 -0.3027115
[367] -0.3028239 -0.3029360 -0.3030480 -0.3031598 -0.3032715 -0.3033830
[373] -0.3034943 -0.3036055 -0.3037164 -0.3038273 -0.3039379 -0.3040484
[379] -0.3041587 -0.3042689 -0.3043789 -0.3044887 -0.3045984 -0.3047079
[385] -0.3048172 -0.3049263 -0.3050353 -0.3051441 -0.3052528 -0.3053613
[391] -0.3054696 -0.3055777 -0.3056857 -0.3057935 -0.3059012 -0.3060087
[397] -0.3061160 -0.3062231 -0.3063301 -0.3064369 -0.3065435
> mx
[1] 0.3065435
> mxli
[1] 2
> if (mxli != 0)
+ {
+ x1 <- (x^mxli - 1) / mxli
+ } else {
+ x1 <- log(x)
+ }
> r<-lm(y~x)
> se <- sqrt(var(r$residuals))
> r1 <- lm(y~x1)
> se1 <- sqrt(var(r1$residuals))
> postscript(file="/var/www/rcomp/tmp/1b6iq1257761229.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(l,c,main='Box-Cox Linearity Plot',xlab='Lambda',ylab='correlation')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/200x91257761229.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(x,y,main='Linear Fit of Original Data',xlab='x',ylab='y')
> abline(r)
> grid()
> mtext(paste('Residual Standard Deviation = ',se))
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/330t51257761229.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(x1,y,main='Linear Fit of Transformed Data',xlab='x',ylab='y')
> abline(r1)
> grid()
> mtext(paste('Residual Standard Deviation = ',se1))
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Box-Cox Linearity Plot',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'# observations x',header=TRUE)
> a<-table.element(a,n)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'maximum correlation',header=TRUE)
> a<-table.element(a,mx)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'optimal lambda(x)',header=TRUE)
> a<-table.element(a,mxli)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Residual SD (orginial)',header=TRUE)
> a<-table.element(a,se)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Residual SD (transformed)',header=TRUE)
> a<-table.element(a,se1)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4tc1m1257761229.tab") 
> 
> system("convert tmp/1b6iq1257761229.ps tmp/1b6iq1257761229.png")
> system("convert tmp/200x91257761229.ps tmp/200x91257761229.png")
> system("convert tmp/330t51257761229.ps tmp/330t51257761229.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.000   0.870   1.729