R version 2.6.0 (2007-10-03)
Copyright (C) 2007 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.

> x <- c(6.5,6.4,6.2,6.2,6.3,7.5,7.4,7.4,7.4,7.4,7.4,7.2,7.2,7.2,7.5,7.4,7.4,8,8.1,8.1,8.1,8.1,8.1,7.9,7.9,8,8.1,8.1,8.1,8.5,8.5,8.6,8.4,8.4,8.4,7.7,7.8,7.9,8.7,8.8,8.8,8.5,8.5,8.5,8.4,8.5,8.5,8.3,8.4,8.4,8.4,8.4,8.4,8.5,8.5,8.5,8.5,8.5,8.5,8.3,8.3,8.4,8.2,8.2,8.1,8.1,8,7.8,7.9,7.8,7.7,7.9,7.8)
> #'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 Normality Plot (v1.0.4) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_boxcoxnorm.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(qnorm(ppoints(x), mean=0, sd=1),x1)
+ if (mx < c[i])
+ {
+ mx <- c[i]
+ mxli <- l[i]
+ }
+ }
> c
  [1] 0.6314453 0.6314278 0.6314101 0.6313921 0.6313739 0.6313554 0.6313367
  [8] 0.6313177 0.6312985 0.6312790 0.6312592 0.6312392 0.6312189 0.6311984
 [15] 0.6311776 0.6311566 0.6311353 0.6311138 0.6310920 0.6310699 0.6310476
 [22] 0.6310250 0.6310022 0.6309791 0.6309557 0.6309321 0.6309083 0.6308842
 [29] 0.6308598 0.6308352 0.6308103 0.6307852 0.6307598 0.6307341 0.6307082
 [36] 0.6306821 0.6306556 0.6306290 0.6306020 0.6305748 0.6305474 0.6305197
 [43] 0.6304917 0.6304635 0.6304350 0.6304063 0.6303773 0.6303481 0.6303186
 [50] 0.6302888 0.6302588 0.6302286 0.6301980 0.6301672 0.6301362 0.6301049
 [57] 0.6300734 0.6300416 0.6300095 0.6299772 0.6299446 0.6299118 0.6298787
 [64] 0.6298453 0.6298117 0.6297779 0.6297438 0.6297094 0.6296748 0.6296399
 [71] 0.6296048 0.6295694 0.6295337 0.6294978 0.6294616 0.6294252 0.6293886
 [78] 0.6293516 0.6293144 0.6292770 0.6292393 0.6292014 0.6291632 0.6291247
 [85] 0.6290860 0.6290470 0.6290078 0.6289683 0.6289286 0.6288886 0.6288483
 [92] 0.6288078 0.6287671 0.6287260 0.6286848 0.6286433 0.6286015 0.6285595
 [99] 0.6285172 0.6284746 0.6284318 0.6283888 0.6283455 0.6283019 0.6282581
[106] 0.6282141 0.6281697 0.6281252 0.6280803 0.6280353 0.6279899 0.6279443
[113] 0.6278985 0.6278524 0.6278061 0.6277595 0.6277126 0.6276655 0.6276182
[120] 0.6275705 0.6275227 0.6274746 0.6274262 0.6273776 0.6273287 0.6272796
[127] 0.6272302 0.6271806 0.6271307 0.6270806 0.6270302 0.6269796 0.6269287
[134] 0.6268775 0.6268262 0.6267745 0.6267226 0.6266705 0.6266181 0.6265655
[141] 0.6265126 0.6264594 0.6264061 0.6263524 0.6262985 0.6262444 0.6261900
[148] 0.6261354 0.6260805 0.6260253 0.6259699 0.6259143 0.6258584 0.6258023
[155] 0.6257459 0.6256893 0.6256324 0.6255753 0.6255179 0.6254603 0.6254024
[162] 0.6253443 0.6252859 0.6252273 0.6251685 0.6251094 0.6250500 0.6249904
[169] 0.6249306 0.6248705 0.6248102 0.6247496 0.6246888 0.6246277 0.6245664
[176] 0.6245048 0.6244430 0.6243809 0.6243186 0.6242561 0.6241933 0.6241303
[183] 0.6240670 0.6240035 0.6239397 0.6238757 0.6238115 0.6237470 0.6236822
[190] 0.6236173 0.6235520 0.6234866 0.6234209 0.6233549 0.6232887 0.6232223
[197] 0.6231556 0.6230887 0.6230216 0.6229542 0.6228865 0.6228187 0.6227505
[204] 0.6226822 0.6226136 0.6225447 0.6224757 0.6224064 0.6223368 0.6222670
[211] 0.6221970 0.6221267 0.6220562 0.6219854 0.6219144 0.6218432 0.6217718
[218] 0.6217001 0.6216281 0.6215559 0.6214835 0.6214109 0.6213380 0.6212649
[225] 0.6211915 0.6211179 0.6210441 0.6209701 0.6208958 0.6208212 0.6207465
[232] 0.6206715 0.6205962 0.6205208 0.6204451 0.6203691 0.6202930 0.6202165
[239] 0.6201399 0.6200630 0.6199859 0.6199086 0.6198311 0.6197533 0.6196752
[246] 0.6195970 0.6195185 0.6194398 0.6193608 0.6192816 0.6192022 0.6191226
[253] 0.6190427 0.6189626 0.6188823 0.6188017 0.6187210 0.6186399 0.6185587
[260] 0.6184772 0.6183955 0.6183136 0.6182315 0.6181491 0.6180665 0.6179837
[267] 0.6179006 0.6178173 0.6177338 0.6176501 0.6175661 0.6174820 0.6173975
[274] 0.6173129 0.6172281 0.6171430 0.6170577 0.6169722 0.6168864 0.6168004
[281] 0.6167143 0.6166278 0.6165412 0.6164543 0.6163673 0.6162800 0.6161924
[288] 0.6161047 0.6160167 0.6159286 0.6158402 0.6157515 0.6156627 0.6155737
[295] 0.6154844 0.6153949 0.6153052 0.6152152 0.6151251 0.6150347 0.6149441
[302] 0.6148533 0.6147623 0.6146711 0.6145797 0.6144880 0.6143961 0.6143040
[309] 0.6142117 0.6141192 0.6140265 0.6139335 0.6138404 0.6137470 0.6136534
[316] 0.6135596 0.6134656 0.6133714 0.6132769 0.6131823 0.6130874 0.6129923
[323] 0.6128971 0.6128016 0.6127059 0.6126100 0.6125139 0.6124175 0.6123210
[330] 0.6122242 0.6121273 0.6120301 0.6119328 0.6118352 0.6117374 0.6116394
[337] 0.6115412 0.6114428 0.6113442 0.6112454 0.6111464 0.6110472 0.6109477
[344] 0.6108481 0.6107483 0.6106482 0.6105480 0.6104475 0.6103469 0.6102461
[351] 0.6101450 0.6100437 0.6099423 0.6098406 0.6097388 0.6096367 0.6095345
[358] 0.6094320 0.6093294 0.6092265 0.6091235 0.6090202 0.6089168 0.6088131
[365] 0.6087093 0.6086052 0.6085010 0.6083966 0.6082919 0.6081871 0.6080821
[372] 0.6079769 0.6078714 0.6077658 0.6076600 0.6075540 0.6074478 0.6073415
[379] 0.6072349 0.6071281 0.6070212 0.6069140 0.6068067 0.6066991 0.6065914
[386] 0.6064835 0.6063754 0.6062671 0.6061586 0.6060499 0.6059411 0.6058320
[393] 0.6057228 0.6056133 0.6055037 0.6053939 0.6052839 0.6051737 0.6050634
[400] 0.6049528 0.6048421
> mx
[1] 0.6314453
> mxli
[1] -2
> if (mxli != 0)
+ {
+ x1 <- (x^mxli - 1) / mxli
+ } else {
+ x1 <- log(x)
+ }
> postscript(file="/var/www/html/rcomp/tmp/1entm1194288584.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(l,c,main='Box-Cox Normality Plot',xlab='Lambda',ylab='correlation')
> mtext(paste('Optimal Lambda =',mxli))
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2nfk01194288584.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(x,main='Histogram of Original Data',xlab='X',ylab='frequency')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3756r1194288584.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(x1,main='Histogram of Transformed Data',xlab='X',ylab='frequency')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4bh0g1194288585.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> grid()
> mtext('Original Data')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/5i5td1194288585.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x1)
> grid()
> mtext('Transformed Data')
> 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 Normality 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',header=TRUE)
> a<-table.element(a,mxli)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/65x0m1194288585.tab") 
> 
> system("convert tmp/1entm1194288584.ps tmp/1entm1194288584.png")
> system("convert tmp/2nfk01194288584.ps tmp/2nfk01194288584.png")
> system("convert tmp/3756r1194288584.ps tmp/3756r1194288584.png")
> system("convert tmp/4bh0g1194288585.ps tmp/4bh0g1194288585.png")
> system("convert tmp/5i5td1194288585.ps tmp/5i5td1194288585.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.359   0.830   1.605