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(103.2,102.9,102.6,102.3,102.1,101.5,101.1,101.9,101.5,101.5,102.0,101.5,101.6,101.5,101.9,102.0,102.0,102.2,102.2,102.3,102.0,101.8,101.8,101.6,101.9,102.3,102.4,102.1,102.3,102.2)
> #'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] -0.1393366 -0.1393559 -0.1393751 -0.1393944 -0.1394137 -0.1394329
  [7] -0.1394522 -0.1394715 -0.1394907 -0.1395100 -0.1395293 -0.1395486
 [13] -0.1395678 -0.1395871 -0.1396064 -0.1396256 -0.1396449 -0.1396642
 [19] -0.1396834 -0.1397027 -0.1397220 -0.1397413 -0.1397605 -0.1397798
 [25] -0.1397991 -0.1398183 -0.1398376 -0.1398569 -0.1398762 -0.1398954
 [31] -0.1399147 -0.1399340 -0.1399532 -0.1399725 -0.1399918 -0.1400111
 [37] -0.1400303 -0.1400496 -0.1400689 -0.1400882 -0.1401074 -0.1401267
 [43] -0.1401460 -0.1401653 -0.1401845 -0.1402038 -0.1402231 -0.1402424
 [49] -0.1402616 -0.1402809 -0.1403002 -0.1403195 -0.1403387 -0.1403580
 [55] -0.1403773 -0.1403966 -0.1404158 -0.1404351 -0.1404544 -0.1404737
 [61] -0.1404929 -0.1405122 -0.1405315 -0.1405508 -0.1405701 -0.1405893
 [67] -0.1406086 -0.1406279 -0.1406472 -0.1406664 -0.1406857 -0.1407050
 [73] -0.1407243 -0.1407436 -0.1407628 -0.1407821 -0.1408014 -0.1408207
 [79] -0.1408400 -0.1408592 -0.1408785 -0.1408978 -0.1409171 -0.1409364
 [85] -0.1409556 -0.1409749 -0.1409942 -0.1410135 -0.1410328 -0.1410521
 [91] -0.1410713 -0.1410906 -0.1411099 -0.1411292 -0.1411485 -0.1411677
 [97] -0.1411870 -0.1412063 -0.1412256 -0.1412449 -0.1412642 -0.1412834
[103] -0.1413027 -0.1413220 -0.1413413 -0.1413606 -0.1413799 -0.1413991
[109] -0.1414184 -0.1414377 -0.1414570 -0.1414763 -0.1414956 -0.1415149
[115] -0.1415341 -0.1415534 -0.1415727 -0.1415920 -0.1416113 -0.1416306
[121] -0.1416499 -0.1416691 -0.1416884 -0.1417077 -0.1417270 -0.1417463
[127] -0.1417656 -0.1417849 -0.1418042 -0.1418234 -0.1418427 -0.1418620
[133] -0.1418813 -0.1419006 -0.1419199 -0.1419392 -0.1419585 -0.1419777
[139] -0.1419970 -0.1420163 -0.1420356 -0.1420549 -0.1420742 -0.1420935
[145] -0.1421128 -0.1421321 -0.1421514 -0.1421706 -0.1421899 -0.1422092
[151] -0.1422285 -0.1422478 -0.1422671 -0.1422864 -0.1423057 -0.1423250
[157] -0.1423443 -0.1423636 -0.1423828 -0.1424021 -0.1424214 -0.1424407
[163] -0.1424600 -0.1424793 -0.1424986 -0.1425179 -0.1425372 -0.1425565
[169] -0.1425758 -0.1425951 -0.1426144 -0.1426337 -0.1426530 -0.1426722
[175] -0.1426915 -0.1427108 -0.1427301 -0.1427494 -0.1427687 -0.1427880
[181] -0.1428073 -0.1428266 -0.1428459 -0.1428652 -0.1428845 -0.1429038
[187] -0.1429231 -0.1429424 -0.1429617 -0.1429810 -0.1430003 -0.1430196
[193] -0.1430389 -0.1430582 -0.1430775 -0.1430968 -0.1431161 -0.1431354
[199] -0.1431546 -0.1431739 -0.1431932 -0.1432125 -0.1432318 -0.1432511
[205] -0.1432704 -0.1432897 -0.1433090 -0.1433283 -0.1433476 -0.1433669
[211] -0.1433862 -0.1434055 -0.1434248 -0.1434441 -0.1434634 -0.1434827
[217] -0.1435020 -0.1435213 -0.1435406 -0.1435599 -0.1435792 -0.1435985
[223] -0.1436178 -0.1436371 -0.1436564 -0.1436757 -0.1436950 -0.1437143
[229] -0.1437336 -0.1437530 -0.1437723 -0.1437916 -0.1438109 -0.1438302
[235] -0.1438495 -0.1438688 -0.1438881 -0.1439074 -0.1439267 -0.1439460
[241] -0.1439653 -0.1439846 -0.1440039 -0.1440232 -0.1440425 -0.1440618
[247] -0.1440811 -0.1441004 -0.1441197 -0.1441390 -0.1441583 -0.1441776
[253] -0.1441969 -0.1442162 -0.1442356 -0.1442549 -0.1442742 -0.1442935
[259] -0.1443128 -0.1443321 -0.1443514 -0.1443707 -0.1443900 -0.1444093
[265] -0.1444286 -0.1444479 -0.1444672 -0.1444865 -0.1445058 -0.1445252
[271] -0.1445445 -0.1445638 -0.1445831 -0.1446024 -0.1446217 -0.1446410
[277] -0.1446603 -0.1446796 -0.1446989 -0.1447182 -0.1447375 -0.1447569
[283] -0.1447762 -0.1447955 -0.1448148 -0.1448341 -0.1448534 -0.1448727
[289] -0.1448920 -0.1449113 -0.1449306 -0.1449500 -0.1449693 -0.1449886
[295] -0.1450079 -0.1450272 -0.1450465 -0.1450658 -0.1450851 -0.1451044
[301] -0.1451238 -0.1451431 -0.1451624 -0.1451817 -0.1452010 -0.1452203
[307] -0.1452396 -0.1452589 -0.1452783 -0.1452976 -0.1453169 -0.1453362
[313] -0.1453555 -0.1453748 -0.1453941 -0.1454135 -0.1454328 -0.1454521
[319] -0.1454714 -0.1454907 -0.1455100 -0.1455293 -0.1455487 -0.1455680
[325] -0.1455873 -0.1456066 -0.1456259 -0.1456452 -0.1456645 -0.1456839
[331] -0.1457032 -0.1457225 -0.1457418 -0.1457611 -0.1457804 -0.1457998
[337] -0.1458191 -0.1458384 -0.1458577 -0.1458770 -0.1458963 -0.1459157
[343] -0.1459350 -0.1459543 -0.1459736 -0.1459929 -0.1460122 -0.1460316
[349] -0.1460509 -0.1460702 -0.1460895 -0.1461088 -0.1461282 -0.1461475
[355] -0.1461668 -0.1461861 -0.1462054 -0.1462248 -0.1462441 -0.1462634
[361] -0.1462827 -0.1463020 -0.1463213 -0.1463407 -0.1463600 -0.1463793
[367] -0.1463986 -0.1464180 -0.1464373 -0.1464566 -0.1464759 -0.1464952
[373] -0.1465146 -0.1465339 -0.1465532 -0.1465725 -0.1465918 -0.1466112
[379] -0.1466305 -0.1466498 -0.1466691 -0.1466885 -0.1467078 -0.1467271
[385] -0.1467464 -0.1467657 -0.1467851 -0.1468044 -0.1468237 -0.1468430
[391] -0.1468624 -0.1468817 -0.1469010 -0.1469203 -0.1469397 -0.1469590
[397] -0.1469783 -0.1469976 -0.1470169 -0.1470363 -0.1470556
> 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/1g3h91226592503.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/28fex1226592503.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/3ove61226592503.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/42mf61226592503.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/51muw1226592503.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/6efxy1226592503.tab") 
> 
> system("convert tmp/1g3h91226592503.ps tmp/1g3h91226592503.png")
> system("convert tmp/28fex1226592503.ps tmp/28fex1226592503.png")
> system("convert tmp/3ove61226592503.ps tmp/3ove61226592503.png")
> system("convert tmp/42mf61226592503.ps tmp/42mf61226592503.png")
> system("convert tmp/51muw1226592503.ps tmp/51muw1226592503.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.382   0.875   2.417