R version 2.8.0 (2008-10-20)
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(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)
> x <- 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)
> #'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] -0.05777247 -0.05794630 -0.05812017 -0.05829409 -0.05846806 -0.05864208
  [7] -0.05881615 -0.05899027 -0.05916443 -0.05933864 -0.05951290 -0.05968720
 [13] -0.05986156 -0.06003596 -0.06021041 -0.06038490 -0.06055944 -0.06073403
 [19] -0.06090866 -0.06108334 -0.06125807 -0.06143284 -0.06160765 -0.06178252
 [25] -0.06195742 -0.06213238 -0.06230737 -0.06248242 -0.06265750 -0.06283264
 [31] -0.06300781 -0.06318303 -0.06335830 -0.06353360 -0.06370896 -0.06388435
 [37] -0.06405979 -0.06423527 -0.06441080 -0.06458636 -0.06476197 -0.06493763
 [43] -0.06511332 -0.06528906 -0.06546484 -0.06564066 -0.06581652 -0.06599243
 [49] -0.06616837 -0.06634436 -0.06652039 -0.06669646 -0.06687257 -0.06704872
 [55] -0.06722491 -0.06740114 -0.06757741 -0.06775372 -0.06793007 -0.06810646
 [61] -0.06828289 -0.06845936 -0.06863586 -0.06881241 -0.06898899 -0.06916562
 [67] -0.06934228 -0.06951898 -0.06969571 -0.06987249 -0.07004930 -0.07022615
 [73] -0.07040304 -0.07057997 -0.07075693 -0.07093393 -0.07111096 -0.07128803
 [79] -0.07146514 -0.07164228 -0.07181946 -0.07199668 -0.07217393 -0.07235122
 [85] -0.07252854 -0.07270589 -0.07288328 -0.07306071 -0.07323817 -0.07341567
 [91] -0.07359319 -0.07377076 -0.07394835 -0.07412599 -0.07430365 -0.07448135
 [97] -0.07465908 -0.07483684 -0.07501464 -0.07519246 -0.07537032 -0.07554822
[103] -0.07572614 -0.07590410 -0.07608209 -0.07626011 -0.07643816 -0.07661624
[109] -0.07679436 -0.07697250 -0.07715068 -0.07732888 -0.07750712 -0.07768538
[115] -0.07786368 -0.07804200 -0.07822036 -0.07839874 -0.07857716 -0.07875560
[121] -0.07893407 -0.07911257 -0.07929110 -0.07946965 -0.07964824 -0.07982685
[127] -0.08000549 -0.08018416 -0.08036285 -0.08054158 -0.08072033 -0.08089910
[133] -0.08107790 -0.08125673 -0.08143559 -0.08161447 -0.08179338 -0.08197231
[139] -0.08215127 -0.08233025 -0.08250926 -0.08268830 -0.08286736 -0.08304644
[145] -0.08322555 -0.08340468 -0.08358384 -0.08376302 -0.08394222 -0.08412145
[151] -0.08430070 -0.08447998 -0.08465927 -0.08483859 -0.08501793 -0.08519730
[157] -0.08537669 -0.08555610 -0.08573553 -0.08591498 -0.08609445 -0.08627395
[163] -0.08645347 -0.08663300 -0.08681256 -0.08699214 -0.08717174 -0.08735136
[169] -0.08753100 -0.08771066 -0.08789034 -0.08807003 -0.08824975 -0.08842949
[175] -0.08860924 -0.08878902 -0.08896881 -0.08914862 -0.08932845 -0.08950830
[181] -0.08968816 -0.08986804 -0.09004794 -0.09022786 -0.09040779 -0.09058774
[187] -0.09076771 -0.09094770 -0.09112770 -0.09130771 -0.09148774 -0.09166779
[193] -0.09184785 -0.09202793 -0.09220802 -0.09238813 -0.09256826 -0.09274839
[199] -0.09292855 -0.09310871 -0.09328889 -0.09346908 -0.09364929 -0.09382951
[205] -0.09400975 -0.09418999 -0.09437025 -0.09455053 -0.09473081 -0.09491111
[211] -0.09509142 -0.09527174 -0.09545207 -0.09563241 -0.09581277 -0.09599314
[217] -0.09617351 -0.09635390 -0.09653430 -0.09671471 -0.09689513 -0.09707556
[223] -0.09725600 -0.09743645 -0.09761690 -0.09779737 -0.09797785 -0.09815833
[229] -0.09833883 -0.09851933 -0.09869984 -0.09888036 -0.09906088 -0.09924142
[235] -0.09942196 -0.09960251 -0.09978306 -0.09996363 -0.10014419 -0.10032477
[241] -0.10050535 -0.10068594 -0.10086654 -0.10104714 -0.10122774 -0.10140835
[247] -0.10158897 -0.10176959 -0.10195021 -0.10213084 -0.10231148 -0.10249212
[253] -0.10267276 -0.10285341 -0.10303406 -0.10321471 -0.10339537 -0.10357603
[259] -0.10375669 -0.10393736 -0.10411803 -0.10429870 -0.10447937 -0.10466004
[265] -0.10484072 -0.10502140 -0.10520208 -0.10538276 -0.10556344 -0.10574412
[271] -0.10592480 -0.10610548 -0.10628616 -0.10646685 -0.10664753 -0.10682821
[277] -0.10700889 -0.10718957 -0.10737025 -0.10755093 -0.10773161 -0.10791228
[283] -0.10809296 -0.10827363 -0.10845430 -0.10863496 -0.10881563 -0.10899629
[289] -0.10917695 -0.10935760 -0.10953826 -0.10971891 -0.10989955 -0.11008019
[295] -0.11026083 -0.11044146 -0.11062209 -0.11080271 -0.11098333 -0.11116395
[301] -0.11134455 -0.11152516 -0.11170575 -0.11188635 -0.11206693 -0.11224751
[307] -0.11242808 -0.11260865 -0.11278921 -0.11296976 -0.11315031 -0.11333084
[313] -0.11351137 -0.11369190 -0.11387241 -0.11405292 -0.11423341 -0.11441390
[319] -0.11459438 -0.11477486 -0.11495532 -0.11513577 -0.11531622 -0.11549665
[325] -0.11567707 -0.11585749 -0.11603789 -0.11621829 -0.11639867 -0.11657904
[331] -0.11675940 -0.11693975 -0.11712009 -0.11730042 -0.11748073 -0.11766103
[337] -0.11784133 -0.11802160 -0.11820187 -0.11838212 -0.11856236 -0.11874259
[343] -0.11892280 -0.11910300 -0.11928319 -0.11946336 -0.11964352 -0.11982366
[349] -0.12000379 -0.12018391 -0.12036401 -0.12054409 -0.12072416 -0.12090421
[355] -0.12108425 -0.12126428 -0.12144428 -0.12162427 -0.12180425 -0.12198420
[361] -0.12216415 -0.12234407 -0.12252398 -0.12270386 -0.12288374 -0.12306359
[367] -0.12324343 -0.12342324 -0.12360304 -0.12378282 -0.12396259 -0.12414233
[373] -0.12432205 -0.12450176 -0.12468145 -0.12486111 -0.12504076 -0.12522038
[379] -0.12539999 -0.12557958 -0.12575914 -0.12593869 -0.12611821 -0.12629771
[385] -0.12647719 -0.12665665 -0.12683609 -0.12701551 -0.12719490 -0.12737427
[391] -0.12755362 -0.12773295 -0.12791225 -0.12809153 -0.12827079 -0.12845002
[397] -0.12862923 -0.12880842 -0.12898758 -0.12916672 -0.12934584
> mx
[1] 0.1293458
> 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/freestat/rcomp/tmp/1anlv1226408397.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/freestat/rcomp/tmp/27s1a1226408397.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/freestat/rcomp/tmp/3zld71226408397.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/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/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/freestat/rcomp/tmp/4xzb81226408397.tab") 
> 
> system("convert tmp/1anlv1226408397.ps tmp/1anlv1226408397.png")
> system("convert tmp/27s1a1226408397.ps tmp/27s1a1226408397.png")
> system("convert tmp/3zld71226408397.ps tmp/3zld71226408397.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.242   0.821   1.345