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(0.800641,0.769764,0.745823,0.762253,0.768403,0.757518,0.772917,0.787774,0.82203,0.830772,0.813537,0.815927,0.832293,0.848464,0.843455,0.826241,0.837661,0.831947,0.81493,0.783085,0.790514,0.788395,0.780579,0.785731,0.792959,0.776337,0.75683,0.76929,0.764877,0.755173,0.739864,0.740138,0.745212,0.729076,0.734107,0.719632,0.702889,0.681013,0.686342,0.67944,0.678058,0.644039,0.63488,0.642797,0.642963,0.634115,0.66778,0.695894,0.750638,0.785423,0.74355,0.755344,0.782167,0.766284,0.75815,0.732601,0.71347,0.709824,0.700869,0.700869)
> x <- c(8.7,8.2,8.3,8.5,8.6,8.5,8.2,8.1,7.9,8.6,8.7,8.7,8.5,8.4,8.5,8.7,8.7,8.6,8.5,8.3,8,8.2,8.1,8.1,8,7.9,7.9,8,8,7.9,8,7.7,7.2,7.5,7.3,7,7,7,7.2,7.3,7.1,6.8,6.4,6.1,6.5,7.7,7.9,7.5,6.9,6.6,6.9,7.7,8,8,7.7,7.3,7.4,8.1,8.3,8.3)
> #'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] 0.7078027 0.7078890 0.7079753 0.7080613 0.7081472 0.7082330 0.7083186
  [8] 0.7084040 0.7084893 0.7085745 0.7086595 0.7087443 0.7088290 0.7089135
 [15] 0.7089978 0.7090820 0.7091661 0.7092500 0.7093337 0.7094173 0.7095008
 [22] 0.7095840 0.7096672 0.7097501 0.7098330 0.7099156 0.7099981 0.7100805
 [29] 0.7101627 0.7102447 0.7103266 0.7104083 0.7104899 0.7105713 0.7106526
 [36] 0.7107337 0.7108147 0.7108955 0.7109761 0.7110566 0.7111370 0.7112171
 [43] 0.7112972 0.7113770 0.7114568 0.7115363 0.7116157 0.7116950 0.7117741
 [50] 0.7118530 0.7119318 0.7120105 0.7120889 0.7121673 0.7122454 0.7123235
 [57] 0.7124013 0.7124790 0.7125566 0.7126340 0.7127112 0.7127883 0.7128652
 [64] 0.7129420 0.7130186 0.7130951 0.7131714 0.7132476 0.7133236 0.7133994
 [71] 0.7134751 0.7135507 0.7136261 0.7137013 0.7137764 0.7138513 0.7139261
 [78] 0.7140007 0.7140751 0.7141495 0.7142236 0.7142976 0.7143714 0.7144451
 [85] 0.7145187 0.7145920 0.7146653 0.7147383 0.7148113 0.7148840 0.7149566
 [92] 0.7150291 0.7151014 0.7151735 0.7152455 0.7153173 0.7153890 0.7154606
 [99] 0.7155319 0.7156032 0.7156742 0.7157451 0.7158159 0.7158865 0.7159569
[106] 0.7160272 0.7160974 0.7161674 0.7162372 0.7163069 0.7163764 0.7164458
[113] 0.7165150 0.7165841 0.7166530 0.7167217 0.7167903 0.7168588 0.7169271
[120] 0.7169952 0.7170632 0.7171311 0.7171987 0.7172663 0.7173336 0.7174009
[127] 0.7174679 0.7175348 0.7176016 0.7176682 0.7177347 0.7178010 0.7178671
[134] 0.7179331 0.7179990 0.7180647 0.7181302 0.7181956 0.7182608 0.7183259
[141] 0.7183908 0.7184556 0.7185202 0.7185847 0.7186490 0.7187132 0.7187772
[148] 0.7188410 0.7189047 0.7189683 0.7190317 0.7190949 0.7191580 0.7192210
[155] 0.7192838 0.7193464 0.7194089 0.7194712 0.7195334 0.7195954 0.7196573
[162] 0.7197190 0.7197806 0.7198420 0.7199033 0.7199644 0.7200254 0.7200862
[169] 0.7201469 0.7202074 0.7202677 0.7203280 0.7203880 0.7204479 0.7205077
[176] 0.7205673 0.7206267 0.7206860 0.7207452 0.7208042 0.7208630 0.7209217
[183] 0.7209803 0.7210387 0.7210969 0.7211550 0.7212129 0.7212707 0.7213284
[190] 0.7213859 0.7214432 0.7215004 0.7215574 0.7216143 0.7216711 0.7217276
[197] 0.7217841 0.7218404 0.7218965 0.7219525 0.7220083 0.7220640 0.7221195
[204] 0.7221749 0.7222302 0.7222853 0.7223402 0.7223950 0.7224496 0.7225041
[211] 0.7225584 0.7226126 0.7226667 0.7227206 0.7227743 0.7228279 0.7228813
[218] 0.7229346 0.7229878 0.7230408 0.7230936 0.7231463 0.7231989 0.7232513
[225] 0.7233035 0.7233556 0.7234076 0.7234594 0.7235111 0.7235626 0.7236139
[232] 0.7236652 0.7237162 0.7237671 0.7238179 0.7238685 0.7239190 0.7239693
[239] 0.7240195 0.7240695 0.7241194 0.7241692 0.7242188 0.7242682 0.7243175
[246] 0.7243666 0.7244156 0.7244645 0.7245132 0.7245618 0.7246102 0.7246584
[253] 0.7247065 0.7247545 0.7248023 0.7248500 0.7248976 0.7249449 0.7249922
[260] 0.7250393 0.7250862 0.7251330 0.7251797 0.7252262 0.7252725 0.7253188
[267] 0.7253648 0.7254108 0.7254565 0.7255022 0.7255477 0.7255930 0.7256382
[274] 0.7256833 0.7257282 0.7257729 0.7258175 0.7258620 0.7259063 0.7259505
[281] 0.7259946 0.7260385 0.7260822 0.7261258 0.7261693 0.7262126 0.7262558
[288] 0.7262988 0.7263417 0.7263844 0.7264270 0.7264694 0.7265118 0.7265539
[295] 0.7265959 0.7266378 0.7266795 0.7267211 0.7267626 0.7268039 0.7268450
[302] 0.7268861 0.7269269 0.7269677 0.7270082 0.7270487 0.7270890 0.7271292
[309] 0.7271692 0.7272090 0.7272488 0.7272884 0.7273278 0.7273671 0.7274063
[316] 0.7274453 0.7274842 0.7275229 0.7275615 0.7276000 0.7276383 0.7276765
[323] 0.7277145 0.7277524 0.7277901 0.7278277 0.7278652 0.7279025 0.7279397
[330] 0.7279767 0.7280137 0.7280504 0.7280870 0.7281235 0.7281599 0.7281961
[337] 0.7282321 0.7282680 0.7283038 0.7283395 0.7283750 0.7284103 0.7284455
[344] 0.7284806 0.7285156 0.7285504 0.7285850 0.7286196 0.7286539 0.7286882
[351] 0.7287223 0.7287563 0.7287901 0.7288238 0.7288573 0.7288908 0.7289240
[358] 0.7289572 0.7289902 0.7290230 0.7290558 0.7290883 0.7291208 0.7291531
[365] 0.7291853 0.7292173 0.7292492 0.7292810 0.7293126 0.7293441 0.7293754
[372] 0.7294066 0.7294377 0.7294686 0.7294994 0.7295301 0.7295606 0.7295910
[379] 0.7296213 0.7296514 0.7296814 0.7297112 0.7297409 0.7297705 0.7298000
[386] 0.7298293 0.7298584 0.7298875 0.7299164 0.7299451 0.7299737 0.7300022
[393] 0.7300306 0.7300588 0.7300869 0.7301149 0.7301427 0.7301704 0.7301979
[400] 0.7302253 0.7302526
> mx
[1] 0.7302526
> 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/1rk5c1258148632.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/218xw1258148632.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/3g8u81258148632.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/4x1jv1258148632.tab") 
> 
> system("convert tmp/1rk5c1258148632.ps tmp/1rk5c1258148632.png")
> system("convert tmp/218xw1258148632.ps tmp/218xw1258148632.png")
> system("convert tmp/3g8u81258148632.ps tmp/3g8u81258148632.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.748   0.516   0.950