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

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> x <- c(100.4,123.3,156.6,136.2,147.5,143.8,135.8,121.6,128,129.7,136.2,130.5,99.2)
> #'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(qnorm(ppoints(x), mean=0, sd=1),x1)
+ if (mx < c[i])
+ {
+ mx <- c[i]
+ mxli <- l[i]
+ }
+ }
> c
  [1] -0.09250100 -0.09262717 -0.09275357 -0.09288019 -0.09300704 -0.09313412
  [7] -0.09326142 -0.09338896 -0.09351672 -0.09364470 -0.09377292 -0.09390136
 [13] -0.09403002 -0.09415891 -0.09428803 -0.09441737 -0.09454694 -0.09467673
 [19] -0.09480675 -0.09493699 -0.09506746 -0.09519815 -0.09532906 -0.09546020
 [25] -0.09559156 -0.09572314 -0.09585495 -0.09598698 -0.09611923 -0.09625170
 [31] -0.09638440 -0.09651732 -0.09665046 -0.09678382 -0.09691740 -0.09705120
 [37] -0.09718522 -0.09731946 -0.09745393 -0.09758861 -0.09772351 -0.09785863
 [43] -0.09799397 -0.09812953 -0.09826530 -0.09840130 -0.09853751 -0.09867394
 [49] -0.09881058 -0.09894744 -0.09908452 -0.09922182 -0.09935933 -0.09949706
 [55] -0.09963500 -0.09977316 -0.09991153 -0.10005012 -0.10018892 -0.10032793
 [61] -0.10046716 -0.10060660 -0.10074626 -0.10088612 -0.10102620 -0.10116649
 [67] -0.10130700 -0.10144771 -0.10158864 -0.10172977 -0.10187112 -0.10201267
 [73] -0.10215444 -0.10229641 -0.10243860 -0.10258099 -0.10272359 -0.10286640
 [79] -0.10300941 -0.10315264 -0.10329607 -0.10343970 -0.10358355 -0.10372759
 [85] -0.10387185 -0.10401631 -0.10416097 -0.10430584 -0.10445091 -0.10459619
 [91] -0.10474166 -0.10488735 -0.10503323 -0.10517932 -0.10532560 -0.10547209
 [97] -0.10561878 -0.10576567 -0.10591276 -0.10606005 -0.10620754 -0.10635523
[103] -0.10650312 -0.10665121 -0.10679949 -0.10694797 -0.10709665 -0.10724552
[109] -0.10739459 -0.10754386 -0.10769332 -0.10784297 -0.10799282 -0.10814287
[115] -0.10829310 -0.10844354 -0.10859416 -0.10874498 -0.10889598 -0.10904718
[121] -0.10919857 -0.10935015 -0.10950192 -0.10965389 -0.10980604 -0.10995837
[127] -0.11011090 -0.11026362 -0.11041652 -0.11056961 -0.11072288 -0.11087635
[133] -0.11102999 -0.11118383 -0.11133784 -0.11149205 -0.11164643 -0.11180100
[139] -0.11195575 -0.11211069 -0.11226580 -0.11242110 -0.11257658 -0.11273224
[145] -0.11288807 -0.11304409 -0.11320029 -0.11335666 -0.11351322 -0.11366995
[151] -0.11382686 -0.11398394 -0.11414120 -0.11429864 -0.11445625 -0.11461403
[157] -0.11477199 -0.11493012 -0.11508843 -0.11524691 -0.11540556 -0.11556438
[163] -0.11572337 -0.11588254 -0.11604187 -0.11620137 -0.11636104 -0.11652088
[169] -0.11668089 -0.11684106 -0.11700140 -0.11716191 -0.11732258 -0.11748342
[175] -0.11764442 -0.11780559 -0.11796692 -0.11812841 -0.11829006 -0.11845188
[181] -0.11861386 -0.11877600 -0.11893830 -0.11910076 -0.11926337 -0.11942615
[187] -0.11958908 -0.11975218 -0.11991542 -0.12007883 -0.12024239 -0.12040610
[193] -0.12056997 -0.12073400 -0.12089818 -0.12106251 -0.12122699 -0.12139162
[199] -0.12155641 -0.12172134 -0.12188643 -0.12205166 -0.12221705 -0.12238258
[205] -0.12254826 -0.12271408 -0.12288006 -0.12304618 -0.12321244 -0.12337885
[211] -0.12354540 -0.12371210 -0.12387893 -0.12404592 -0.12421304 -0.12438030
[217] -0.12454771 -0.12471525 -0.12488293 -0.12505075 -0.12521871 -0.12538681
[223] -0.12555504 -0.12572341 -0.12589192 -0.12606056 -0.12622933 -0.12639824
[229] -0.12656728 -0.12673645 -0.12690575 -0.12707519 -0.12724476 -0.12741445
[235] -0.12758428 -0.12775423 -0.12792431 -0.12809452 -0.12826486 -0.12843532
[241] -0.12860591 -0.12877662 -0.12894745 -0.12911841 -0.12928950 -0.12946070
[247] -0.12963203 -0.12980347 -0.12997504 -0.13014672 -0.13031853 -0.13049045
[253] -0.13066249 -0.13083465 -0.13100693 -0.13117932 -0.13135182 -0.13152444
[259] -0.13169717 -0.13187002 -0.13204298 -0.13221605 -0.13238923 -0.13256252
[265] -0.13273592 -0.13290943 -0.13308305 -0.13325678 -0.13343061 -0.13360455
[271] -0.13377859 -0.13395274 -0.13412699 -0.13430135 -0.13447581 -0.13465038
[277] -0.13482504 -0.13499980 -0.13517467 -0.13534963 -0.13552470 -0.13569986
[283] -0.13587512 -0.13605047 -0.13622593 -0.13640147 -0.13657712 -0.13675285
[289] -0.13692868 -0.13710460 -0.13728062 -0.13745672 -0.13763292 -0.13780920
[295] -0.13798558 -0.13816204 -0.13833859 -0.13851523 -0.13869196 -0.13886877
[301] -0.13904566 -0.13922264 -0.13939970 -0.13957685 -0.13975408 -0.13993139
[307] -0.14010878 -0.14028625 -0.14046380 -0.14064143 -0.14081913 -0.14099692
[313] -0.14117478 -0.14135271 -0.14153073 -0.14170881 -0.14188697 -0.14206520
[319] -0.14224351 -0.14242188 -0.14260033 -0.14277885 -0.14295744 -0.14313609
[325] -0.14331481 -0.14349361 -0.14367246 -0.14385139 -0.14403038 -0.14420943
[331] -0.14438855 -0.14456773 -0.14474697 -0.14492627 -0.14510564 -0.14528506
[337] -0.14546455 -0.14564409 -0.14582369 -0.14600335 -0.14618306 -0.14636283
[343] -0.14654266 -0.14672254 -0.14690247 -0.14708246 -0.14726250 -0.14744259
[349] -0.14762273 -0.14780293 -0.14798317 -0.14816346 -0.14834380 -0.14852418
[355] -0.14870461 -0.14888509 -0.14906562 -0.14924618 -0.14942679 -0.14960745
[361] -0.14978814 -0.14996888 -0.15014966 -0.15033048 -0.15051134 -0.15069223
[367] -0.15087317 -0.15105414 -0.15123515 -0.15141619 -0.15159727 -0.15177838
[373] -0.15195953 -0.15214071 -0.15232192 -0.15250316 -0.15268444 -0.15286574
[379] -0.15304708 -0.15322844 -0.15340983 -0.15359124 -0.15377269 -0.15395416
[385] -0.15413565 -0.15431717 -0.15449871 -0.15468027 -0.15486186 -0.15504347
[391] -0.15522510 -0.15540675 -0.15558841 -0.15577010 -0.15595180 -0.15613353
[397] -0.15631526 -0.15649702 -0.15667878 -0.15686057 -0.15704236
> mx
[1] 0
> mxli
[1] -999
> if (mxli != 0)
+ {
+ x1 <- (x^mxli - 1) / mxli
+ } else {
+ x1 <- log(x)
+ }
> postscript(file="/var/www/html/rcomp/tmp/1f5t61226521758.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/2i0ob1226521758.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/3kehu1226521758.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/4wxiw1226521758.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> qqline(x)
> grid()
> mtext('Original Data')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/5x9r91226521758.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x1)
> qqline(x1)
> grid()
> mtext('Transformed Data')
> 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 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/6jeac1226521758.tab") 
> 
> system("convert tmp/1f5t61226521758.ps tmp/1f5t61226521758.png")
> system("convert tmp/2i0ob1226521758.ps tmp/2i0ob1226521758.png")
> system("convert tmp/3kehu1226521758.ps tmp/3kehu1226521758.png")
> system("convert tmp/4wxiw1226521758.ps tmp/4wxiw1226521758.png")
> system("convert tmp/5x9r91226521758.ps tmp/5x9r91226521758.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.323   0.811   1.556