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(100.6,104.3,120.4,107.5,102.9,125.6,107.5,108.8,128.4,121.1,119.5,128.7,108.7,105.5,119.8,111.3,110.6,120.1,97.5,107.7,127.3,117.2,119.8,116.2,111,112.4,130.6,109.1,118.8,123.9,101.6,112.8,128,129.6,125.8,119.5,115.7,113.6,129.7,112,116.8,127,112.1,114.2,121.1,131.6,125,120.4,117.7,117.5,120.6,127.5,112.3,124.5,115.2,104.7,130.9,129.2,113.5,125.6,107.6)
> x <- c(95.1,97,112.7,102.9,97.4,111.4,87.4,96.8,114.1,110.3,103.9,101.6,94.6,95.9,104.7,102.8,98.1,113.9,80.9,95.7,113.2,105.9,108.8,102.3,99,100.7,115.5,100.7,109.9,114.6,85.4,100.5,114.8,116.5,112.9,102,106,105.3,118.8,106.1,109.3,117.2,92.5,104.2,112.5,122.4,113.3,100,110.7,112.8,109.8,117.3,109.1,115.9,96,99.8,116.8,115.7,99.4,94.3,91)
> #'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] 0.8072494 0.8073793 0.8075090 0.8076383 0.8077674 0.8078962 0.8080247
  [8] 0.8081530 0.8082809 0.8084085 0.8085359 0.8086630 0.8087898 0.8089163
 [15] 0.8090425 0.8091684 0.8092941 0.8094194 0.8095445 0.8096693 0.8097938
 [22] 0.8099180 0.8100419 0.8101655 0.8102889 0.8104120 0.8105348 0.8106573
 [29] 0.8107795 0.8109014 0.8110230 0.8111444 0.8112655 0.8113862 0.8115068
 [36] 0.8116270 0.8117469 0.8118665 0.8119859 0.8121050 0.8122238 0.8123423
 [43] 0.8124605 0.8125785 0.8126961 0.8128135 0.8129306 0.8130474 0.8131639
 [50] 0.8132802 0.8133961 0.8135118 0.8136272 0.8137423 0.8138571 0.8139717
 [57] 0.8140859 0.8141999 0.8143136 0.8144270 0.8145402 0.8146530 0.8147656
 [64] 0.8148779 0.8149899 0.8151016 0.8152130 0.8153242 0.8154351 0.8155457
 [71] 0.8156560 0.8157660 0.8158758 0.8159853 0.8160945 0.8162034 0.8163120
 [78] 0.8164204 0.8165285 0.8166363 0.8167438 0.8168510 0.8169580 0.8170647
 [85] 0.8171711 0.8172772 0.8173831 0.8174886 0.8175939 0.8176989 0.8178037
 [92] 0.8179081 0.8180123 0.8181162 0.8182198 0.8183232 0.8184263 0.8185291
 [99] 0.8186316 0.8187338 0.8188358 0.8189375 0.8190389 0.8191400 0.8192409
[106] 0.8193415 0.8194418 0.8195418 0.8196416 0.8197411 0.8198403 0.8199393
[113] 0.8200379 0.8201363 0.8202344 0.8203323 0.8204299 0.8205272 0.8206242
[120] 0.8207209 0.8208174 0.8209136 0.8210096 0.8211052 0.8212006 0.8212957
[127] 0.8213906 0.8214852 0.8215795 0.8216735 0.8217673 0.8218607 0.8219540
[134] 0.8220469 0.8221396 0.8222320 0.8223242 0.8224160 0.8225076 0.8225990
[141] 0.8226900 0.8227808 0.8228714 0.8229616 0.8230516 0.8231413 0.8232308
[148] 0.8233200 0.8234089 0.8234976 0.8235860 0.8236741 0.8237619 0.8238495
[155] 0.8239368 0.8240239 0.8241107 0.8241972 0.8242835 0.8243695 0.8244552
[162] 0.8245407 0.8246259 0.8247108 0.8247955 0.8248799 0.8249640 0.8250479
[169] 0.8251315 0.8252149 0.8252980 0.8253808 0.8254634 0.8255457 0.8256277
[176] 0.8257095 0.8257911 0.8258723 0.8259533 0.8260341 0.8261145 0.8261948
[183] 0.8262747 0.8263544 0.8264339 0.8265130 0.8265920 0.8266706 0.8267490
[190] 0.8268272 0.8269051 0.8269827 0.8270601 0.8271372 0.8272140 0.8272906
[197] 0.8273670 0.8274431 0.8275189 0.8275945 0.8276698 0.8277449 0.8278197
[204] 0.8278942 0.8279685 0.8280426 0.8281163 0.8281899 0.8282632 0.8283362
[211] 0.8284090 0.8284815 0.8285538 0.8286258 0.8286975 0.8287690 0.8288403
[218] 0.8289113 0.8289821 0.8290526 0.8291228 0.8291928 0.8292626 0.8293321
[225] 0.8294013 0.8294703 0.8295391 0.8296076 0.8296758 0.8297438 0.8298116
[232] 0.8298791 0.8299463 0.8300133 0.8300801 0.8301466 0.8302129 0.8302789
[239] 0.8303447 0.8304102 0.8304755 0.8305405 0.8306053 0.8306699 0.8307342
[246] 0.8307982 0.8308620 0.8309256 0.8309889 0.8310520 0.8311148 0.8311774
[253] 0.8312398 0.8313019 0.8313637 0.8314254 0.8314867 0.8315479 0.8316088
[260] 0.8316694 0.8317298 0.8317900 0.8318499 0.8319096 0.8319691 0.8320283
[267] 0.8320873 0.8321460 0.8322045 0.8322627 0.8323208 0.8323785 0.8324361
[274] 0.8324934 0.8325504 0.8326073 0.8326639 0.8327202 0.8327763 0.8328322
[281] 0.8328879 0.8329433 0.8329984 0.8330534 0.8331081 0.8331626 0.8332168
[288] 0.8332708 0.8333246 0.8333781 0.8334314 0.8334845 0.8335373 0.8335899
[295] 0.8336423 0.8336944 0.8337463 0.8337980 0.8338495 0.8339007 0.8339516
[302] 0.8340024 0.8340529 0.8341032 0.8341533 0.8342031 0.8342527 0.8343021
[309] 0.8343513 0.8344002 0.8344489 0.8344973 0.8345456 0.8345936 0.8346414
[316] 0.8346889 0.8347362 0.8347834 0.8348302 0.8348769 0.8349233 0.8349695
[323] 0.8350155 0.8350612 0.8351068 0.8351521 0.8351972 0.8352420 0.8352867
[330] 0.8353311 0.8353753 0.8354192 0.8354630 0.8355065 0.8355498 0.8355929
[337] 0.8356358 0.8356784 0.8357208 0.8357630 0.8358050 0.8358467 0.8358883
[344] 0.8359296 0.8359707 0.8360116 0.8360523 0.8360927 0.8361329 0.8361730
[351] 0.8362128 0.8362523 0.8362917 0.8363308 0.8363698 0.8364085 0.8364470
[358] 0.8364853 0.8365233 0.8365612 0.8365988 0.8366362 0.8366735 0.8367105
[365] 0.8367472 0.8367838 0.8368202 0.8368563 0.8368922 0.8369280 0.8369635
[372] 0.8369988 0.8370338 0.8370687 0.8371034 0.8371378 0.8371721 0.8372061
[379] 0.8372399 0.8372736 0.8373070 0.8373402 0.8373731 0.8374059 0.8374385
[386] 0.8374709 0.8375030 0.8375350 0.8375667 0.8375982 0.8376296 0.8376607
[393] 0.8376916 0.8377223 0.8377528 0.8377831 0.8378132 0.8378431 0.8378728
[400] 0.8379023 0.8379316
> mx
[1] 0.8379316
> 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/11n421260809659.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/2md001260809659.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/3mb631260809659.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/4pcfw1260809659.tab") 
> try(system("convert tmp/11n421260809659.ps tmp/11n421260809659.png",intern=TRUE))
character(0)
> try(system("convert tmp/2md001260809659.ps tmp/2md001260809659.png",intern=TRUE))
character(0)
> try(system("convert tmp/3mb631260809659.ps tmp/3mb631260809659.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.800   0.510   1.322