R version 2.5.1 (2007-06-27)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(4.8,-4.2,1.6,5.2,9.2,4.6,10.6)
> x <- c(0.9,0.85,0.83,0.84,0.85,0.83,0.83)
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa P., (2007), Box-Cox Linearity Plot (v1.0.3) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_boxcoxlin.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description
> 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] -0.08664121 -0.08661167 -0.08658212 -0.08655258 -0.08652304 -0.08649350
  [7] -0.08646395 -0.08643442 -0.08640488 -0.08637534 -0.08634580 -0.08631627
 [13] -0.08628674 -0.08625720 -0.08622767 -0.08619814 -0.08616861 -0.08613908
 [19] -0.08610956 -0.08608003 -0.08605050 -0.08602098 -0.08599146 -0.08596194
 [25] -0.08593242 -0.08590290 -0.08587338 -0.08584386 -0.08581435 -0.08578483
 [31] -0.08575532 -0.08572581 -0.08569630 -0.08566679 -0.08563728 -0.08560777
 [37] -0.08557827 -0.08554876 -0.08551926 -0.08548975 -0.08546025 -0.08543075
 [43] -0.08540125 -0.08537176 -0.08534226 -0.08531277 -0.08528327 -0.08525378
 [49] -0.08522429 -0.08519480 -0.08516531 -0.08513582 -0.08510633 -0.08507685
 [55] -0.08504737 -0.08501788 -0.08498840 -0.08495892 -0.08492944 -0.08489997
 [61] -0.08487049 -0.08484101 -0.08481154 -0.08478207 -0.08475260 -0.08472313
 [67] -0.08469366 -0.08466419 -0.08463473 -0.08460526 -0.08457580 -0.08454634
 [73] -0.08451688 -0.08448742 -0.08445796 -0.08442850 -0.08439905 -0.08436959
 [79] -0.08434014 -0.08431069 -0.08428124 -0.08425179 -0.08422235 -0.08419290
 [85] -0.08416346 -0.08413401 -0.08410457 -0.08407513 -0.08404569 -0.08401626
 [91] -0.08398682 -0.08395739 -0.08392795 -0.08389852 -0.08386909 -0.08383966
 [97] -0.08381024 -0.08378081 -0.08375138 -0.08372196 -0.08369254 -0.08366312
[103] -0.08363370 -0.08360428 -0.08357487 -0.08354545 -0.08351604 -0.08348663
[109] -0.08345722 -0.08342781 -0.08339840 -0.08336900 -0.08333959 -0.08331019
[115] -0.08328079 -0.08325139 -0.08322199 -0.08319259 -0.08316320 -0.08313381
[121] -0.08310441 -0.08307502 -0.08304563 -0.08301625 -0.08298686 -0.08295747
[127] -0.08292809 -0.08289871 -0.08286933 -0.08283995 -0.08281057 -0.08278120
[133] -0.08275183 -0.08272245 -0.08269308 -0.08266371 -0.08263435 -0.08260498
[139] -0.08257562 -0.08254625 -0.08251689 -0.08248753 -0.08245817 -0.08242882
[145] -0.08239946 -0.08237011 -0.08234076 -0.08231141 -0.08228206 -0.08225271
[151] -0.08222337 -0.08219402 -0.08216468 -0.08213534 -0.08210600 -0.08207666
[157] -0.08204733 -0.08201799 -0.08198866 -0.08195933 -0.08193000 -0.08190068
[163] -0.08187135 -0.08184203 -0.08181270 -0.08178338 -0.08175406 -0.08172475
[169] -0.08169543 -0.08166612 -0.08163680 -0.08160749 -0.08157819 -0.08154888
[175] -0.08151957 -0.08149027 -0.08146097 -0.08143167 -0.08140237 -0.08137307
[181] -0.08134378 -0.08131448 -0.08128519 -0.08125590 -0.08122661 -0.08119733
[187] -0.08116804 -0.08113876 -0.08110948 -0.08108020 -0.08105092 -0.08102164
[193] -0.08099237 -0.08096310 -0.08093383 -0.08090456 -0.08087529 -0.08084603
[199] -0.08081676 -0.08078750 -0.08075824 -0.08072898 -0.08069973 -0.08067047
[205] -0.08064122 -0.08061197 -0.08058272 -0.08055347 -0.08052423 -0.08049498
[211] -0.08046574 -0.08043650 -0.08040726 -0.08037803 -0.08034879 -0.08031956
[217] -0.08029033 -0.08026110 -0.08023187 -0.08020265 -0.08017342 -0.08014420
[223] -0.08011498 -0.08008577 -0.08005655 -0.08002734 -0.07999812 -0.07996891
[229] -0.07993971 -0.07991050 -0.07988130 -0.07985209 -0.07982289 -0.07979369
[235] -0.07976450 -0.07973530 -0.07970611 -0.07967692 -0.07964773 -0.07961854
[241] -0.07958936 -0.07956017 -0.07953099 -0.07950181 -0.07947263 -0.07944346
[247] -0.07941429 -0.07938511 -0.07935594 -0.07932678 -0.07929761 -0.07926845
[253] -0.07923929 -0.07921013 -0.07918097 -0.07915181 -0.07912266 -0.07909351
[259] -0.07906436 -0.07903521 -0.07900606 -0.07897692 -0.07894778 -0.07891864
[265] -0.07888950 -0.07886037 -0.07883123 -0.07880210 -0.07877297 -0.07874384
[271] -0.07871472 -0.07868560 -0.07865647 -0.07862735 -0.07859824 -0.07856912
[277] -0.07854001 -0.07851090 -0.07848179 -0.07845268 -0.07842358 -0.07839447
[283] -0.07836537 -0.07833628 -0.07830718 -0.07827808 -0.07824899 -0.07821990
[289] -0.07819081 -0.07816173 -0.07813264 -0.07810356 -0.07807448 -0.07804540
[295] -0.07801633 -0.07798726 -0.07795819 -0.07792912 -0.07790005 -0.07787098
[301] -0.07784192 -0.07781286 -0.07778380 -0.07775475 -0.07772569 -0.07769664
[307] -0.07766759 -0.07763854 -0.07760950 -0.07758046 -0.07755142 -0.07752238
[313] -0.07749334 -0.07746431 -0.07743527 -0.07740624 -0.07737722 -0.07734819
[319] -0.07731917 -0.07729015 -0.07726113 -0.07723211 -0.07720310 -0.07717408
[325] -0.07714507 -0.07711607 -0.07708706 -0.07705806 -0.07702906 -0.07700006
[331] -0.07697106 -0.07694207 -0.07691307 -0.07688408 -0.07685510 -0.07682611
[337] -0.07679713 -0.07676815 -0.07673917 -0.07671019 -0.07668122 -0.07665225
[343] -0.07662328 -0.07659431 -0.07656535 -0.07653638 -0.07650742 -0.07647847
[349] -0.07644951 -0.07642056 -0.07639161 -0.07636266 -0.07633371 -0.07630477
[355] -0.07627583 -0.07624689 -0.07621795 -0.07618902 -0.07616008 -0.07613115
[361] -0.07610223 -0.07607330 -0.07604438 -0.07601546 -0.07598654 -0.07595762
[367] -0.07592871 -0.07589980 -0.07587089 -0.07584199 -0.07581308 -0.07578418
[373] -0.07575528 -0.07572639 -0.07569749 -0.07566860 -0.07563971 -0.07561082
[379] -0.07558194 -0.07555306 -0.07552418 -0.07549530 -0.07546642 -0.07543755
[385] -0.07540868 -0.07537981 -0.07535095 -0.07532209 -0.07529323 -0.07526437
[391] -0.07523551 -0.07520666 -0.07517781 -0.07514896 -0.07512012 -0.07509127
[397] -0.07506243 -0.07503359 -0.07500476 -0.07497593 -0.07494710
> mx
[1] 0.08664121
> 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/1hiu81193407478.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/2vj8y1193407478.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/3hgoh1193407478.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 
> 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/4tv4b1193407478.tab") 
> 
> system("convert tmp/1hiu81193407478.ps tmp/1hiu81193407478.png")
> system("convert tmp/2vj8y1193407478.ps tmp/2vj8y1193407478.png")
> system("convert tmp/3hgoh1193407478.ps tmp/3hgoh1193407478.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.046   0.497   1.181