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

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> y <- c(1.1663,1.1372,1.1139,1.1222,1.1692,1.1702,1.2286,1.2613,1.2646,1.2262,1.1985,1.2007,1.2138,1.2266,1.2176,1.2218,1.249,1.2991,1.3408,1.3119,1.3014,1.3201,1.2938,1.2694,1.2165,1.2037,1.2292,1.2256,1.2015,1.1786,1.1856,1.2103,1.1938,1.202,1.2271,1.277,1.265,1.2684,1.2811,1.2727,1.2611,1.2881,1.3213,1.2999,1.3074,1.3242,1.3516,1.3511,1.3419,1.3716,1.3622,1.3896,1.4227,1.4684,1.457,1.4718,1.4748,1.5527,1.575,1.5557,1.5553)
> x <- c(604.4,883.9,527.9,756.2,812.9,655.6,707.6,612.6,659.2,833.4,727.8,797.2,753,762,613.7,759.2,816.4,736.8,680.1,736.5,637.2,801.9,772.3,897.3,792.1,826.8,666.8,906.6,871.4,891,739.2,833.6,715.6,871.6,751.6,1005.5,681.2,837.3,674.7,806.3,860.2,689.8,691.6,682.6,800.1,1023.7,733.5,875.3,770.2,1005.7,982.3,742.9,974.2,822.3,773.2,750.9,708,690,652.8,620.7,461.9)
> #'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] -0.17864585 -0.17844836 -0.17825059 -0.17805255 -0.17785424 -0.17765566
  [7] -0.17745680 -0.17725768 -0.17705828 -0.17685862 -0.17665868 -0.17645848
 [13] -0.17625802 -0.17605729 -0.17585629 -0.17565503 -0.17545350 -0.17525172
 [19] -0.17504967 -0.17484736 -0.17464479 -0.17444197 -0.17423888 -0.17403554
 [25] -0.17383194 -0.17362808 -0.17342398 -0.17321961 -0.17301500 -0.17281013
 [31] -0.17260501 -0.17239964 -0.17219403 -0.17198816 -0.17178205 -0.17157569
 [37] -0.17136908 -0.17116223 -0.17095514 -0.17074780 -0.17054022 -0.17033240
 [43] -0.17012435 -0.16991605 -0.16970751 -0.16949874 -0.16928973 -0.16908048
 [49] -0.16887100 -0.16866129 -0.16845134 -0.16824117 -0.16803076 -0.16782012
 [55] -0.16760926 -0.16739816 -0.16718684 -0.16697530 -0.16676353 -0.16655154
 [61] -0.16633932 -0.16612688 -0.16591422 -0.16570135 -0.16548825 -0.16527493
 [67] -0.16506140 -0.16484766 -0.16463369 -0.16441952 -0.16420513 -0.16399053
 [73] -0.16377572 -0.16356070 -0.16334547 -0.16313004 -0.16291439 -0.16269855
 [79] -0.16248249 -0.16226624 -0.16204978 -0.16183312 -0.16161626 -0.16139920
 [85] -0.16118194 -0.16096448 -0.16074683 -0.16052899 -0.16031094 -0.16009271
 [91] -0.15987428 -0.15965567 -0.15943686 -0.15921786 -0.15899868 -0.15877930
 [97] -0.15855975 -0.15834000 -0.15812008 -0.15789997 -0.15767968 -0.15745921
[103] -0.15723856 -0.15701773 -0.15679672 -0.15657554 -0.15635418 -0.15613265
[109] -0.15591094 -0.15568906 -0.15546701 -0.15524479 -0.15502241 -0.15479985
[115] -0.15457713 -0.15435424 -0.15413118 -0.15390796 -0.15368458 -0.15346104
[121] -0.15323734 -0.15301348 -0.15278945 -0.15256528 -0.15234094 -0.15211645
[127] -0.15189181 -0.15166701 -0.15144206 -0.15121696 -0.15099171 -0.15076631
[133] -0.15054076 -0.15031506 -0.15008922 -0.14986323 -0.14963710 -0.14941083
[139] -0.14918442 -0.14895786 -0.14873117 -0.14850434 -0.14827737 -0.14805026
[145] -0.14782302 -0.14759564 -0.14736813 -0.14714049 -0.14691271 -0.14668481
[151] -0.14645678 -0.14622861 -0.14600033 -0.14577191 -0.14554337 -0.14531471
[157] -0.14508592 -0.14485701 -0.14462798 -0.14439883 -0.14416956 -0.14394018
[163] -0.14371067 -0.14348105 -0.14325132 -0.14302147 -0.14279151 -0.14256144
[169] -0.14233126 -0.14210096 -0.14187056 -0.14164005 -0.14140944 -0.14117871
[175] -0.14094789 -0.14071696 -0.14048592 -0.14025479 -0.14002355 -0.13979222
[181] -0.13956078 -0.13932925 -0.13909762 -0.13886590 -0.13863408 -0.13840217
[187] -0.13817016 -0.13793806 -0.13770587 -0.13747360 -0.13724123 -0.13700877
[193] -0.13677623 -0.13654360 -0.13631089 -0.13607809 -0.13584521 -0.13561224
[199] -0.13537920 -0.13514607 -0.13491287 -0.13467959 -0.13444623 -0.13421279
[205] -0.13397928 -0.13374569 -0.13351203 -0.13327830 -0.13304449 -0.13281062
[211] -0.13257667 -0.13234266 -0.13210857 -0.13187442 -0.13164021 -0.13140593
[217] -0.13117158 -0.13093717 -0.13070270 -0.13046816 -0.13023357 -0.12999891
[223] -0.12976420 -0.12952943 -0.12929460 -0.12905971 -0.12882477 -0.12858978
[229] -0.12835473 -0.12811963 -0.12788447 -0.12764927 -0.12741401 -0.12717871
[235] -0.12694336 -0.12670796 -0.12647251 -0.12623702 -0.12600148 -0.12576590
[241] -0.12553027 -0.12529461 -0.12505890 -0.12482315 -0.12458736 -0.12435153
[247] -0.12411567 -0.12387976 -0.12364382 -0.12340785 -0.12317184 -0.12293579
[253] -0.12269972 -0.12246361 -0.12222747 -0.12199130 -0.12175509 -0.12151886
[259] -0.12128260 -0.12104632 -0.12081000 -0.12057367 -0.12033730 -0.12010091
[265] -0.11986450 -0.11962807 -0.11939161 -0.11915513 -0.11891864 -0.11868212
[271] -0.11844558 -0.11820903 -0.11797246 -0.11773587 -0.11749927 -0.11726265
[277] -0.11702602 -0.11678937 -0.11655272 -0.11631605 -0.11607937 -0.11584267
[283] -0.11560597 -0.11536926 -0.11513255 -0.11489582 -0.11465909 -0.11442235
[289] -0.11418561 -0.11394886 -0.11371211 -0.11347536 -0.11323860 -0.11300184
[295] -0.11276508 -0.11252832 -0.11229157 -0.11205481 -0.11181805 -0.11158130
[301] -0.11134455 -0.11110781 -0.11087107 -0.11063434 -0.11039761 -0.11016089
[307] -0.10992417 -0.10968747 -0.10945077 -0.10921408 -0.10897741 -0.10874074
[313] -0.10850409 -0.10826745 -0.10803082 -0.10779420 -0.10755760 -0.10732102
[319] -0.10708445 -0.10684789 -0.10661136 -0.10637484 -0.10613833 -0.10590185
[325] -0.10566539 -0.10542895 -0.10519253 -0.10495613 -0.10471975 -0.10448339
[331] -0.10424706 -0.10401075 -0.10377447 -0.10353821 -0.10330198 -0.10306577
[337] -0.10282959 -0.10259344 -0.10235732 -0.10212122 -0.10188516 -0.10164912
[343] -0.10141312 -0.10117715 -0.10094121 -0.10070530 -0.10046942 -0.10023358
[349] -0.09999778 -0.09976200 -0.09952627 -0.09929057 -0.09905490 -0.09881928
[355] -0.09858369 -0.09834814 -0.09811262 -0.09787715 -0.09764172 -0.09740633
[361] -0.09717098 -0.09693567 -0.09670040 -0.09646518 -0.09623000 -0.09599486
[367] -0.09575977 -0.09552473 -0.09528973 -0.09505477 -0.09481986 -0.09458500
[373] -0.09435019 -0.09411542 -0.09388071 -0.09364604 -0.09341143 -0.09317686
[379] -0.09294235 -0.09270788 -0.09247347 -0.09223911 -0.09200481 -0.09177056
[385] -0.09153636 -0.09130222 -0.09106813 -0.09083410 -0.09060012 -0.09036620
[391] -0.09013234 -0.08989853 -0.08966479 -0.08943110 -0.08919747 -0.08896390
[397] -0.08873040 -0.08849695 -0.08826356 -0.08803024 -0.08779697
> mx
[1] 0.1786459
> 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/1g1sa1226407588.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/2kc1e1226407588.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/39u2n1226407588.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/4olrg1226407588.tab") 
> 
> system("convert tmp/1g1sa1226407588.ps tmp/1g1sa1226407588.png")
> system("convert tmp/2kc1e1226407588.ps tmp/2kc1e1226407588.png")
> system("convert tmp/39u2n1226407588.ps tmp/39u2n1226407588.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.028   0.513   1.233