R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(100,102.03,103.45,103.33,103.42,104.40,105.89,107.19,108.95,110.95)
> x <- c(100,100.13,100.42,100.88,101.34,101.79,102.44,103.38,104.42,105.29)
> #'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] 0.9778594 0.9778605 0.9778615 0.9778626 0.9778636 0.9778647 0.9778657
  [8] 0.9778667 0.9778678 0.9778688 0.9778698 0.9778708 0.9778718 0.9778728
 [15] 0.9778738 0.9778748 0.9778758 0.9778768 0.9778778 0.9778787 0.9778797
 [22] 0.9778807 0.9778816 0.9778826 0.9778835 0.9778845 0.9778854 0.9778864
 [29] 0.9778873 0.9778882 0.9778892 0.9778901 0.9778910 0.9778919 0.9778928
 [36] 0.9778937 0.9778946 0.9778955 0.9778964 0.9778973 0.9778982 0.9778991
 [43] 0.9778999 0.9779008 0.9779017 0.9779025 0.9779034 0.9779042 0.9779051
 [50] 0.9779059 0.9779068 0.9779076 0.9779084 0.9779093 0.9779101 0.9779109
 [57] 0.9779117 0.9779125 0.9779133 0.9779141 0.9779149 0.9779157 0.9779165
 [64] 0.9779173 0.9779180 0.9779188 0.9779196 0.9779204 0.9779211 0.9779219
 [71] 0.9779226 0.9779234 0.9779241 0.9779248 0.9779256 0.9779263 0.9779270
 [78] 0.9779277 0.9779285 0.9779292 0.9779299 0.9779306 0.9779313 0.9779320
 [85] 0.9779326 0.9779333 0.9779340 0.9779347 0.9779354 0.9779360 0.9779367
 [92] 0.9779373 0.9779380 0.9779386 0.9779393 0.9779399 0.9779406 0.9779412
 [99] 0.9779418 0.9779424 0.9779431 0.9779437 0.9779443 0.9779449 0.9779455
[106] 0.9779461 0.9779467 0.9779472 0.9779478 0.9779484 0.9779490 0.9779495
[113] 0.9779501 0.9779507 0.9779512 0.9779518 0.9779523 0.9779529 0.9779534
[120] 0.9779539 0.9779545 0.9779550 0.9779555 0.9779560 0.9779565 0.9779570
[127] 0.9779575 0.9779580 0.9779585 0.9779590 0.9779595 0.9779600 0.9779605
[134] 0.9779609 0.9779614 0.9779619 0.9779623 0.9779628 0.9779632 0.9779637
[141] 0.9779641 0.9779645 0.9779650 0.9779654 0.9779658 0.9779662 0.9779666
[148] 0.9779671 0.9779675 0.9779679 0.9779683 0.9779686 0.9779690 0.9779694
[155] 0.9779698 0.9779702 0.9779705 0.9779709 0.9779713 0.9779716 0.9779720
[162] 0.9779723 0.9779726 0.9779730 0.9779733 0.9779736 0.9779740 0.9779743
[169] 0.9779746 0.9779749 0.9779752 0.9779755 0.9779758 0.9779761 0.9779764
[176] 0.9779767 0.9779770 0.9779772 0.9779775 0.9779778 0.9779780 0.9779783
[183] 0.9779786 0.9779788 0.9779790 0.9779793 0.9779795 0.9779798 0.9779800
[190] 0.9779802 0.9779804 0.9779806 0.9779808 0.9779810 0.9779812 0.9779814
[197] 0.9779816 0.9779818 0.9779820 0.9779822 0.9779824 0.9779825 0.9779827
[204] 0.9779828 0.9779830 0.9779832 0.9779833 0.9779834 0.9779836 0.9779837
[211] 0.9779838 0.9779840 0.9779841 0.9779842 0.9779843 0.9779844 0.9779845
[218] 0.9779846 0.9779847 0.9779848 0.9779849 0.9779850 0.9779850 0.9779851
[225] 0.9779852 0.9779852 0.9779853 0.9779853 0.9779854 0.9779854 0.9779855
[232] 0.9779855 0.9779855 0.9779856 0.9779856 0.9779856 0.9779856 0.9779856
[239] 0.9779856 0.9779856 0.9779856 0.9779856 0.9779856 0.9779856 0.9779856
[246] 0.9779855 0.9779855 0.9779855 0.9779854 0.9779854 0.9779853 0.9779853
[253] 0.9779852 0.9779852 0.9779851 0.9779850 0.9779849 0.9779849 0.9779848
[260] 0.9779847 0.9779846 0.9779845 0.9779844 0.9779843 0.9779842 0.9779841
[267] 0.9779839 0.9779838 0.9779837 0.9779836 0.9779834 0.9779833 0.9779831
[274] 0.9779830 0.9779828 0.9779827 0.9779825 0.9779823 0.9779821 0.9779820
[281] 0.9779818 0.9779816 0.9779814 0.9779812 0.9779810 0.9779808 0.9779806
[288] 0.9779804 0.9779802 0.9779799 0.9779797 0.9779795 0.9779792 0.9779790
[295] 0.9779788 0.9779785 0.9779783 0.9779780 0.9779777 0.9779775 0.9779772
[302] 0.9779769 0.9779766 0.9779764 0.9779761 0.9779758 0.9779755 0.9779752
[309] 0.9779749 0.9779745 0.9779742 0.9779739 0.9779736 0.9779733 0.9779729
[316] 0.9779726 0.9779722 0.9779719 0.9779715 0.9779712 0.9779708 0.9779705
[323] 0.9779701 0.9779697 0.9779693 0.9779689 0.9779686 0.9779682 0.9779678
[330] 0.9779674 0.9779670 0.9779666 0.9779661 0.9779657 0.9779653 0.9779649
[337] 0.9779644 0.9779640 0.9779636 0.9779631 0.9779627 0.9779622 0.9779617
[344] 0.9779613 0.9779608 0.9779603 0.9779599 0.9779594 0.9779589 0.9779584
[351] 0.9779579 0.9779574 0.9779569 0.9779564 0.9779559 0.9779554 0.9779549
[358] 0.9779543 0.9779538 0.9779533 0.9779527 0.9779522 0.9779516 0.9779511
[365] 0.9779505 0.9779500 0.9779494 0.9779488 0.9779482 0.9779477 0.9779471
[372] 0.9779465 0.9779459 0.9779453 0.9779447 0.9779441 0.9779435 0.9779429
[379] 0.9779422 0.9779416 0.9779410 0.9779404 0.9779397 0.9779391 0.9779384
[386] 0.9779378 0.9779371 0.9779365 0.9779358 0.9779351 0.9779345 0.9779338
[393] 0.9779331 0.9779324 0.9779317 0.9779310 0.9779303 0.9779296 0.9779289
[400] 0.9779282 0.9779275
> mx
[1] 0.9779856
> mxli
[1] 0.38
> 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/1i6xe1258097113.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/27rqo1258097113.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/3vkx71258097113.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/4wny71258097113.tab") 
> 
> system("convert tmp/1i6xe1258097113.ps tmp/1i6xe1258097113.png")
> system("convert tmp/27rqo1258097113.ps tmp/27rqo1258097113.png")
> system("convert tmp/3vkx71258097113.ps tmp/3vkx71258097113.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.778   0.501   1.527