R version 2.7.2 (2008-08-25)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(110.4,112.9,109.4,111.9,108.9,113.8,114.5,113.2,111,114.6,113.1,113.2,115.1,117.6,117.8,115.7,115.7,118.3,117.9,117.3,119.4,117.1,119,120,118.9,116,115.6,119.7,119.7,120.8,120,120.2,121.7,116.9,122.4,122.6,123.7,120.9,124.2,122.6,125.7,123.1,122.2,126.2,124.4,127.8,124.2,126.7,126.1,128.2,130.4,130.2,129.2,129.7,131,129.2,131.1,132.9,135.2,132.3)
> x <- c(101.5,101.3,99.3,100.6,101.2,99.8,100.6,101.1,101.2,101.5,102.2,102.5,101.4,103.8,105.2,105.3,104.4,104.9,106.9,107.6,106.7,106.1,106.3,105.8,104.4,103.8,102.4,103.3,103.5,104.5,103.5,103.9,103.1,102.2,104.7,105.9,106.6,106.6,107.5,107.2,109,108.4,107,108,110.8,110.9,109.7,111,111.5,111,111.8,111.4,110.8,111.9,112.9,111.8,111,112.3,112.4,111.1)
> #'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] 0.9237424 0.9237567 0.9237709 0.9237852 0.9237994 0.9238136 0.9238277
  [8] 0.9238419 0.9238560 0.9238701 0.9238842 0.9238983 0.9239123 0.9239263
 [15] 0.9239403 0.9239543 0.9239682 0.9239821 0.9239960 0.9240099 0.9240238
 [22] 0.9240376 0.9240514 0.9240652 0.9240789 0.9240927 0.9241064 0.9241201
 [29] 0.9241338 0.9241474 0.9241611 0.9241747 0.9241883 0.9242018 0.9242154
 [36] 0.9242289 0.9242424 0.9242558 0.9242693 0.9242827 0.9242961 0.9243095
 [43] 0.9243229 0.9243362 0.9243495 0.9243628 0.9243761 0.9243893 0.9244026
 [50] 0.9244158 0.9244289 0.9244421 0.9244552 0.9244683 0.9244814 0.9244945
 [57] 0.9245075 0.9245206 0.9245336 0.9245466 0.9245595 0.9245724 0.9245854
 [64] 0.9245982 0.9246111 0.9246239 0.9246368 0.9246496 0.9246623 0.9246751
 [71] 0.9246878 0.9247005 0.9247132 0.9247259 0.9247385 0.9247512 0.9247637
 [78] 0.9247763 0.9247889 0.9248014 0.9248139 0.9248264 0.9248389 0.9248513
 [85] 0.9248637 0.9248761 0.9248885 0.9249008 0.9249132 0.9249255 0.9249377
 [92] 0.9249500 0.9249622 0.9249745 0.9249867 0.9249988 0.9250110 0.9250231
 [99] 0.9250352 0.9250473 0.9250593 0.9250714 0.9250834 0.9250954 0.9251074
[106] 0.9251193 0.9251312 0.9251431 0.9251550 0.9251669 0.9251787 0.9251905
[113] 0.9252023 0.9252141 0.9252258 0.9252375 0.9252492 0.9252609 0.9252726
[120] 0.9252842 0.9252958 0.9253074 0.9253190 0.9253305 0.9253420 0.9253535
[127] 0.9253650 0.9253765 0.9253879 0.9253993 0.9254107 0.9254221 0.9254334
[134] 0.9254447 0.9254560 0.9254673 0.9254786 0.9254898 0.9255010 0.9255122
[141] 0.9255234 0.9255345 0.9255456 0.9255567 0.9255678 0.9255788 0.9255899
[148] 0.9256009 0.9256119 0.9256228 0.9256338 0.9256447 0.9256556 0.9256665
[155] 0.9256773 0.9256881 0.9256990 0.9257097 0.9257205 0.9257312 0.9257420
[162] 0.9257527 0.9257633 0.9257740 0.9257846 0.9257952 0.9258058 0.9258164
[169] 0.9258269 0.9258374 0.9258479 0.9258584 0.9258688 0.9258793 0.9258897
[176] 0.9259001 0.9259104 0.9259208 0.9259311 0.9259414 0.9259517 0.9259619
[183] 0.9259721 0.9259823 0.9259925 0.9260027 0.9260128 0.9260229 0.9260330
[190] 0.9260431 0.9260532 0.9260632 0.9260732 0.9260832 0.9260931 0.9261031
[197] 0.9261130 0.9261229 0.9261328 0.9261426 0.9261525 0.9261623 0.9261720
[204] 0.9261818 0.9261915 0.9262013 0.9262110 0.9262206 0.9262303 0.9262399
[211] 0.9262495 0.9262591 0.9262687 0.9262782 0.9262877 0.9262972 0.9263067
[218] 0.9263161 0.9263256 0.9263350 0.9263444 0.9263537 0.9263631 0.9263724
[225] 0.9263817 0.9263910 0.9264002 0.9264095 0.9264187 0.9264278 0.9264370
[232] 0.9264462 0.9264553 0.9264644 0.9264734 0.9264825 0.9264915 0.9265005
[239] 0.9265095 0.9265185 0.9265274 0.9265364 0.9265453 0.9265541 0.9265630
[246] 0.9265718 0.9265806 0.9265894 0.9265982 0.9266069 0.9266157 0.9266244
[253] 0.9266330 0.9266417 0.9266503 0.9266589 0.9266675 0.9266761 0.9266846
[260] 0.9266932 0.9267017 0.9267101 0.9267186 0.9267270 0.9267355 0.9267438
[267] 0.9267522 0.9267606 0.9267689 0.9267772 0.9267855 0.9267937 0.9268020
[274] 0.9268102 0.9268184 0.9268266 0.9268347 0.9268428 0.9268509 0.9268590
[281] 0.9268671 0.9268751 0.9268831 0.9268911 0.9268991 0.9269071 0.9269150
[288] 0.9269229 0.9269308 0.9269387 0.9269465 0.9269543 0.9269621 0.9269699
[295] 0.9269777 0.9269854 0.9269931 0.9270008 0.9270085 0.9270161 0.9270237
[302] 0.9270313 0.9270389 0.9270465 0.9270540 0.9270615 0.9270690 0.9270765
[309] 0.9270839 0.9270913 0.9270987 0.9271061 0.9271135 0.9271208 0.9271281
[316] 0.9271354 0.9271427 0.9271500 0.9271572 0.9271644 0.9271716 0.9271788
[323] 0.9271859 0.9271930 0.9272001 0.9272072 0.9272142 0.9272213 0.9272283
[330] 0.9272353 0.9272423 0.9272492 0.9272561 0.9272630 0.9272699 0.9272768
[337] 0.9272836 0.9272904 0.9272972 0.9273040 0.9273107 0.9273175 0.9273242
[344] 0.9273308 0.9273375 0.9273442 0.9273508 0.9273574 0.9273639 0.9273705
[351] 0.9273770 0.9273835 0.9273900 0.9273965 0.9274029 0.9274094 0.9274158
[358] 0.9274222 0.9274285 0.9274348 0.9274412 0.9274475 0.9274537 0.9274600
[365] 0.9274662 0.9274724 0.9274786 0.9274848 0.9274909 0.9274970 0.9275031
[372] 0.9275092 0.9275153 0.9275213 0.9275273 0.9275333 0.9275393 0.9275452
[379] 0.9275511 0.9275570 0.9275629 0.9275688 0.9275746 0.9275804 0.9275862
[386] 0.9275920 0.9275978 0.9276035 0.9276092 0.9276149 0.9276206 0.9276262
[393] 0.9276318 0.9276374 0.9276430 0.9276486 0.9276541 0.9276596 0.9276651
[400] 0.9276706 0.9276760
> mx
[1] 0.927676
> 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/html/rcomp/tmp/11d1t1226432485.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/html/rcomp/tmp/2rdbl1226432485.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/html/rcomp/tmp/3sbtj1226432485.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/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/html/rcomp/tmp/4yesp1226432485.tab") 
> 
> system("convert tmp/11d1t1226432485.ps tmp/11d1t1226432485.png")
> system("convert tmp/2rdbl1226432485.ps tmp/2rdbl1226432485.png")
> system("convert tmp/3sbtj1226432485.ps tmp/3sbtj1226432485.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.052   0.518   1.210