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(79.8,83.4,113.6,112.9,104,109.9,99,106.3,128.9,111.1,102.9,130,87,87.5,117.6,103.4,110.8,112.6,102.5,112.4,135.6,105.1,127.7,137,91,90.5,122.4,123.3,124.3,120,118.1,119,142.7,123.6,129.6,151.6,110.4,99.2,130.5,136.2,129.7,128,121.6,135.8,143.8,147.5,136.2,156.6,123.3,104.5,139.8,136.5,112.1,118.5,94.4,102.3,111.4,99.2,87.8,115.8)
> x <- c(109.87,95.74,123.06,123.39,120.28,115.33,110.4,114.49,132.03,123.16,118.82,128.32,112.24,104.53,132.57,122.52,131.8,124.55,120.96,122.6,145.52,118.57,134.25,136.7,121.37,111.63,134.42,137.65,137.86,119.77,130.69,128.28,147.45,128.42,136.9,143.95,135.64,122.48,136.83,153.04,142.71,123.46,144.37,146.15,147.61,158.51,147.4,165.05,154.64,126.2,157.36,154.15,123.21,113.07,110.45,113.57,122.44,114.93,111.85,126.04)
> #'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] 0.8760623 0.8761664 0.8762698 0.8763726 0.8764748 0.8765764 0.8766774
  [8] 0.8767778 0.8768776 0.8769768 0.8770754 0.8771735 0.8772709 0.8773677
 [15] 0.8774639 0.8775595 0.8776545 0.8777489 0.8778427 0.8779359 0.8780285
 [22] 0.8781205 0.8782119 0.8783028 0.8783930 0.8784826 0.8785717 0.8786601
 [29] 0.8787480 0.8788352 0.8789219 0.8790079 0.8790934 0.8791783 0.8792626
 [36] 0.8793463 0.8794294 0.8795119 0.8795938 0.8796752 0.8797559 0.8798361
 [43] 0.8799156 0.8799946 0.8800730 0.8801508 0.8802280 0.8803046 0.8803807
 [50] 0.8804562 0.8805310 0.8806053 0.8806790 0.8807521 0.8808247 0.8808966
 [57] 0.8809680 0.8810388 0.8811090 0.8811786 0.8812476 0.8813161 0.8813840
 [64] 0.8814513 0.8815180 0.8815842 0.8816497 0.8817147 0.8817791 0.8818430
 [71] 0.8819062 0.8819689 0.8820310 0.8820925 0.8821535 0.8822139 0.8822737
 [78] 0.8823329 0.8823916 0.8824497 0.8825072 0.8825641 0.8826205 0.8826763
 [85] 0.8827316 0.8827862 0.8828403 0.8828939 0.8829468 0.8829992 0.8830511
 [92] 0.8831023 0.8831530 0.8832032 0.8832528 0.8833018 0.8833502 0.8833981
 [99] 0.8834454 0.8834922 0.8835384 0.8835840 0.8836291 0.8836736 0.8837176
[106] 0.8837610 0.8838038 0.8838461 0.8838878 0.8839290 0.8839696 0.8840096
[113] 0.8840491 0.8840881 0.8841265 0.8841643 0.8842016 0.8842384 0.8842745
[120] 0.8843102 0.8843453 0.8843798 0.8844138 0.8844472 0.8844801 0.8845125
[127] 0.8845442 0.8845755 0.8846062 0.8846364 0.8846660 0.8846950 0.8847236
[134] 0.8847515 0.8847790 0.8848059 0.8848322 0.8848581 0.8848833 0.8849081
[141] 0.8849323 0.8849559 0.8849790 0.8850016 0.8850237 0.8850452 0.8850662
[148] 0.8850866 0.8851065 0.8851259 0.8851447 0.8851630 0.8851808 0.8851981
[155] 0.8852148 0.8852310 0.8852466 0.8852618 0.8852764 0.8852904 0.8853040
[162] 0.8853170 0.8853295 0.8853415 0.8853529 0.8853638 0.8853742 0.8853841
[169] 0.8853935 0.8854023 0.8854106 0.8854184 0.8854257 0.8854324 0.8854387
[176] 0.8854444 0.8854496 0.8854543 0.8854584 0.8854621 0.8854652 0.8854679
[183] 0.8854700 0.8854716 0.8854727 0.8854732 0.8854733 0.8854729 0.8854719
[190] 0.8854705 0.8854685 0.8854660 0.8854630 0.8854595 0.8854556 0.8854511
[197] 0.8854461 0.8854406 0.8854345 0.8854280 0.8854210 0.8854135 0.8854055
[204] 0.8853970 0.8853880 0.8853785 0.8853685 0.8853580 0.8853470 0.8853355
[211] 0.8853235 0.8853110 0.8852980 0.8852845 0.8852706 0.8852561 0.8852412
[218] 0.8852257 0.8852098 0.8851934 0.8851765 0.8851591 0.8851412 0.8851229
[225] 0.8851040 0.8850847 0.8850649 0.8850446 0.8850238 0.8850025 0.8849808
[232] 0.8849585 0.8849358 0.8849126 0.8848890 0.8848648 0.8848402 0.8848151
[239] 0.8847895 0.8847635 0.8847370 0.8847100 0.8846825 0.8846545 0.8846261
[246] 0.8845972 0.8845679 0.8845380 0.8845077 0.8844770 0.8844457 0.8844140
[253] 0.8843819 0.8843492 0.8843161 0.8842825 0.8842485 0.8842140 0.8841791
[260] 0.8841436 0.8841078 0.8840714 0.8840346 0.8839974 0.8839597 0.8839215
[267] 0.8838828 0.8838438 0.8838042 0.8837642 0.8837238 0.8836829 0.8836415
[274] 0.8835997 0.8835574 0.8835147 0.8834715 0.8834279 0.8833839 0.8833394
[281] 0.8832944 0.8832490 0.8832031 0.8831568 0.8831101 0.8830629 0.8830153
[288] 0.8829672 0.8829187 0.8828698 0.8828204 0.8827705 0.8827203 0.8826696
[295] 0.8826184 0.8825668 0.8825148 0.8824623 0.8824095 0.8823561 0.8823024
[302] 0.8822482 0.8821936 0.8821385 0.8820830 0.8820271 0.8819708 0.8819140
[309] 0.8818568 0.8817992 0.8817411 0.8816826 0.8816237 0.8815644 0.8815046
[316] 0.8814445 0.8813839 0.8813228 0.8812614 0.8811995 0.8811373 0.8810746
[323] 0.8810114 0.8809479 0.8808839 0.8808196 0.8807548 0.8806896 0.8806240
[330] 0.8805580 0.8804915 0.8804247 0.8803574 0.8802898 0.8802217 0.8801532
[337] 0.8800843 0.8800150 0.8799453 0.8798752 0.8798046 0.8797337 0.8796624
[344] 0.8795906 0.8795185 0.8794460 0.8793730 0.8792997 0.8792259 0.8791518
[351] 0.8790773 0.8790023 0.8789270 0.8788513 0.8787751 0.8786986 0.8786217
[358] 0.8785444 0.8784667 0.8783886 0.8783101 0.8782312 0.8781520 0.8780723
[365] 0.8779923 0.8779118 0.8778310 0.8777498 0.8776682 0.8775863 0.8775039
[372] 0.8774211 0.8773380 0.8772545 0.8771706 0.8770863 0.8770017 0.8769167
[379] 0.8768312 0.8767455 0.8766593 0.8765727 0.8764858 0.8763985 0.8763109
[386] 0.8762228 0.8761344 0.8760456 0.8759564 0.8758669 0.8757770 0.8756867
[393] 0.8755961 0.8755051 0.8754137 0.8753220 0.8752298 0.8751374 0.8750445
[400] 0.8749513 0.8748577
> mx
[1] 0.8854733
> mxli
[1] -0.14
> 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/14kk41257679889.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/2vndp1257679889.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/3120r1257679889.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/4499a1257679889.tab") 
> 
> system("convert tmp/14kk41257679889.ps tmp/14kk41257679889.png")
> system("convert tmp/2vndp1257679889.ps tmp/2vndp1257679889.png")
> system("convert tmp/3120r1257679889.ps tmp/3120r1257679889.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.791   0.514   0.972