R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(105.9,117.6,113.6,115.9,118.9,77.6,81.2,123.1,136.6,112.1,95.1,96.3,105.7,115,105.7,105.7,111.1,82.4,60,107.3,99.3,113.5,108.9,100.2,103.9,138.7,120.2,100.2,143.2,70.9,85.2,133,136.6,117.9,106.3,122.3,125.5,148.4,126.3,99.6,140.4,80.3,92.6,138.5,110.9,119.6,105,109,129.4,148.6,101.4,134.8,143.7,81.6,90.3,141.5,140.7,140.2,100.2,125.7,119.6,134.7,109,116.3,146.9,97.4,89.4,132.1,139.8,129,112.5,121.9,121.7,123.1,131.6,119.3,132.5,98.3,85.1,131.7,129.3,90.7,78.6,68.9,79.1)
> x <- c(107.25,105.80,102.90,100.00,98.55,108.70,110.14,113.04,115.94,117.39,118.84,120.29,118.84,115.94,114.49,110.14,110.14,120.29,121.74,121.74,121.74,121.74,124.64,128.99,127.54,120.29,108.70,104.35,107.25,127.54,134.78,134.78,126.09,118.84,120.29,123.19,124.64,123.19,118.84,117.39,114.49,124.64,126.09,126.09,123.19,121.74,123.19,126.09,126.09,124.64,123.19,120.29,115.94,118.84,117.39,117.39,115.94,114.49,114.49,115.94,115.94,114.49,115.94,111.59,104.35,108.70,105.80,101.45,101.45,101.45,104.35,105.80,102.90,98.55,92.75,88.41,94.20,111.59,114.49,108.70,100.00,95.65,100.00,111.59,115.94)
> #'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] -0.1288385 -0.1288276 -0.1288166 -0.1288057 -0.1287947 -0.1287836
  [7] -0.1287725 -0.1287614 -0.1287502 -0.1287390 -0.1287278 -0.1287165
 [13] -0.1287052 -0.1286939 -0.1286825 -0.1286711 -0.1286596 -0.1286481
 [19] -0.1286366 -0.1286250 -0.1286134 -0.1286017 -0.1285901 -0.1285783
 [25] -0.1285666 -0.1285548 -0.1285429 -0.1285311 -0.1285192 -0.1285072
 [31] -0.1284952 -0.1284832 -0.1284712 -0.1284591 -0.1284470 -0.1284348
 [37] -0.1284226 -0.1284104 -0.1283981 -0.1283858 -0.1283734 -0.1283611
 [43] -0.1283486 -0.1283362 -0.1283237 -0.1283112 -0.1282986 -0.1282860
 [49] -0.1282734 -0.1282607 -0.1282480 -0.1282353 -0.1282225 -0.1282097
 [55] -0.1281968 -0.1281839 -0.1281710 -0.1281581 -0.1281451 -0.1281320
 [61] -0.1281190 -0.1281059 -0.1280928 -0.1280796 -0.1280664 -0.1280532
 [67] -0.1280399 -0.1280266 -0.1280132 -0.1279999 -0.1279865 -0.1279730
 [73] -0.1279595 -0.1279460 -0.1279325 -0.1279189 -0.1279053 -0.1278916
 [79] -0.1278779 -0.1278642 -0.1278505 -0.1278367 -0.1278228 -0.1278090
 [85] -0.1277951 -0.1277812 -0.1277672 -0.1277532 -0.1277392 -0.1277251
 [91] -0.1277110 -0.1276969 -0.1276827 -0.1276685 -0.1276543 -0.1276401
 [97] -0.1276258 -0.1276114 -0.1275971 -0.1275827 -0.1275682 -0.1275538
[103] -0.1275393 -0.1275248 -0.1275102 -0.1274956 -0.1274810 -0.1274663
[109] -0.1274516 -0.1274369 -0.1274221 -0.1274073 -0.1273925 -0.1273777
[115] -0.1273628 -0.1273478 -0.1273329 -0.1273179 -0.1273029 -0.1272878
[121] -0.1272727 -0.1272576 -0.1272425 -0.1272273 -0.1272121 -0.1271968
[127] -0.1271816 -0.1271663 -0.1271509 -0.1271355 -0.1271201 -0.1271047
[133] -0.1270892 -0.1270737 -0.1270582 -0.1270427 -0.1270271 -0.1270114
[139] -0.1269958 -0.1269801 -0.1269644 -0.1269486 -0.1269329 -0.1269170
[145] -0.1269012 -0.1268853 -0.1268694 -0.1268535 -0.1268375 -0.1268215
[151] -0.1268055 -0.1267894 -0.1267734 -0.1267572 -0.1267411 -0.1267249
[157] -0.1267087 -0.1266925 -0.1266762 -0.1266599 -0.1266436 -0.1266272
[163] -0.1266108 -0.1265944 -0.1265779 -0.1265615 -0.1265450 -0.1265284
[169] -0.1265118 -0.1264952 -0.1264786 -0.1264620 -0.1264453 -0.1264285
[175] -0.1264118 -0.1263950 -0.1263782 -0.1263614 -0.1263445 -0.1263276
[181] -0.1263107 -0.1262938 -0.1262768 -0.1262598 -0.1262427 -0.1262257
[187] -0.1262086 -0.1261914 -0.1261743 -0.1261571 -0.1261399 -0.1261226
[193] -0.1261054 -0.1260881 -0.1260708 -0.1260534 -0.1260360 -0.1260186
[199] -0.1260012 -0.1259837 -0.1259662 -0.1259487 -0.1259311 -0.1259136
[205] -0.1258960 -0.1258783 -0.1258607 -0.1258430 -0.1258252 -0.1258075
[211] -0.1257897 -0.1257719 -0.1257541 -0.1257362 -0.1257184 -0.1257005
[217] -0.1256825 -0.1256646 -0.1256466 -0.1256285 -0.1256105 -0.1255924
[223] -0.1255743 -0.1255562 -0.1255380 -0.1255199 -0.1255017 -0.1254834
[229] -0.1254652 -0.1254469 -0.1254286 -0.1254102 -0.1253919 -0.1253735
[235] -0.1253550 -0.1253366 -0.1253181 -0.1252996 -0.1252811 -0.1252626
[241] -0.1252440 -0.1252254 -0.1252067 -0.1251881 -0.1251694 -0.1251507
[247] -0.1251320 -0.1251132 -0.1250944 -0.1250756 -0.1250568 -0.1250379
[253] -0.1250190 -0.1250001 -0.1249812 -0.1249622 -0.1249432 -0.1249242
[259] -0.1249052 -0.1248861 -0.1248670 -0.1248479 -0.1248288 -0.1248096
[265] -0.1247904 -0.1247712 -0.1247520 -0.1247327 -0.1247134 -0.1246941
[271] -0.1246748 -0.1246554 -0.1246361 -0.1246166 -0.1245972 -0.1245778
[277] -0.1245583 -0.1245388 -0.1245192 -0.1244997 -0.1244801 -0.1244605
[283] -0.1244409 -0.1244212 -0.1244016 -0.1243819 -0.1243621 -0.1243424
[289] -0.1243226 -0.1243028 -0.1242830 -0.1242632 -0.1242433 -0.1242234
[295] -0.1242035 -0.1241836 -0.1241636 -0.1241437 -0.1241236 -0.1241036
[301] -0.1240836 -0.1240635 -0.1240434 -0.1240233 -0.1240031 -0.1239830
[307] -0.1239628 -0.1239426 -0.1239224 -0.1239021 -0.1238818 -0.1238615
[313] -0.1238412 -0.1238209 -0.1238005 -0.1237801 -0.1237597 -0.1237393
[319] -0.1237188 -0.1236983 -0.1236778 -0.1236573 -0.1236368 -0.1236162
[325] -0.1235956 -0.1235750 -0.1235544 -0.1235337 -0.1235130 -0.1234923
[331] -0.1234716 -0.1234509 -0.1234301 -0.1234093 -0.1233885 -0.1233677
[337] -0.1233469 -0.1233260 -0.1233051 -0.1232842 -0.1232633 -0.1232423
[343] -0.1232213 -0.1232003 -0.1231793 -0.1231583 -0.1231372 -0.1231161
[349] -0.1230950 -0.1230739 -0.1230528 -0.1230316 -0.1230104 -0.1229892
[355] -0.1229680 -0.1229468 -0.1229255 -0.1229042 -0.1228829 -0.1228616
[361] -0.1228402 -0.1228189 -0.1227975 -0.1227761 -0.1227547 -0.1227332
[367] -0.1227117 -0.1226903 -0.1226688 -0.1226472 -0.1226257 -0.1226041
[373] -0.1225825 -0.1225609 -0.1225393 -0.1225177 -0.1224960 -0.1224743
[379] -0.1224526 -0.1224309 -0.1224092 -0.1223874 -0.1223656 -0.1223438
[385] -0.1223220 -0.1223002 -0.1222783 -0.1222564 -0.1222345 -0.1222126
[391] -0.1221907 -0.1221688 -0.1221468 -0.1221248 -0.1221028 -0.1220808
[397] -0.1220587 -0.1220367 -0.1220146 -0.1219925 -0.1219704
> mx
[1] 0.1288385
> 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/1kx2z1258123730.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/254qi1258123730.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/3qtdu1258123730.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/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 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/4cw2v1258123730.tab") 
> 
> system("convert tmp/1kx2z1258123730.ps tmp/1kx2z1258123730.png")
> system("convert tmp/254qi1258123730.ps tmp/254qi1258123730.png")
> system("convert tmp/3qtdu1258123730.ps tmp/3qtdu1258123730.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.824   0.513   0.961