R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(46,62,66,59,58,61,41,27,58,70,49,59,44,36,72,45,56,54,53,35,61,52,47,51,52,63,74,45,51,64,36,30,55,64,39,40,63,45,59,55,40,64,27,28,45,57,45,69,60,56,58,50,51,53,37,22,55,70,62,58,39,49,58,47,42,62,39,40,72,70,54,65)
> par5 = 'No'
> par4 = '0'
> par3 = '2'
> par2 = '-1'
> par1 = 'Full Box-Cox transform'
> par5 <- 'No'
> par4 <- '0'
> par3 <- '2'
> par2 <- '-1'
> par1 <- 'Full Box-Cox transform'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 ()
> #Author: root
> #To cite this work: Wessa P., (2013), Box-Cox Normality Plot (v1.1.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_boxcoxnorm.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> par2 <- abs(as.numeric(par2)*100)
> par3 <- as.numeric(par3)*100
> if(par4=='') par4 <- 0
> par4 <- as.numeric(par4)
> numlam <- par2 + par3 + 1
> x <- x + par4
> n <- length(x)
> c <- array(NA,dim=c(numlam))
> l <- array(NA,dim=c(numlam))
> mx <- -1
> mxli <- -999
> for (i in 1:numlam)
+ {
+ l[i] <- (i-par2-1)/100
+ if (l[i] != 0)
+ {
+ if (par1 == 'Full Box-Cox transform') x1 <- (x^l[i] - 1) / l[i]
+ if (par1 == 'Simple Box-Cox transform') x1 <- x^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]
+ x1.best <- x1
+ }
+ }
> c
  [1] -1.005659e-02 -9.956708e-03 -9.856809e-03 -9.756889e-03 -9.656949e-03
  [6] -9.556989e-03 -9.457008e-03 -9.357008e-03 -9.256989e-03 -9.156949e-03
 [11] -9.056891e-03 -8.956814e-03 -8.856717e-03 -8.756603e-03 -8.656469e-03
 [16] -8.556318e-03 -8.456148e-03 -8.355961e-03 -8.255756e-03 -8.155534e-03
 [21] -8.055294e-03 -7.955038e-03 -7.854765e-03 -7.754475e-03 -7.654168e-03
 [26] -7.553846e-03 -7.453507e-03 -7.353153e-03 -7.252783e-03 -7.152398e-03
 [31] -7.051998e-03 -6.951582e-03 -6.851152e-03 -6.750707e-03 -6.650248e-03
 [36] -6.549775e-03 -6.449288e-03 -6.348787e-03 -6.248272e-03 -6.147744e-03
 [41] -6.047203e-03 -5.946649e-03 -5.846083e-03 -5.745503e-03 -5.644912e-03
 [46] -5.544308e-03 -5.443693e-03 -5.343065e-03 -5.242427e-03 -5.141777e-03
 [51] -5.041116e-03 -4.940444e-03 -4.839761e-03 -4.739068e-03 -4.638365e-03
 [56] -4.537651e-03 -4.436928e-03 -4.336195e-03 -4.235453e-03 -4.134701e-03
 [61] -4.033941e-03 -3.933172e-03 -3.832394e-03 -3.731607e-03 -3.630813e-03
 [66] -3.530010e-03 -3.429200e-03 -3.328382e-03 -3.227557e-03 -3.126725e-03
 [71] -3.025886e-03 -2.925040e-03 -2.824187e-03 -2.723329e-03 -2.622464e-03
 [76] -2.521593e-03 -2.420717e-03 -2.319835e-03 -2.218948e-03 -2.118055e-03
 [81] -2.017158e-03 -1.916257e-03 -1.815351e-03 -1.714440e-03 -1.613526e-03
 [86] -1.512608e-03 -1.411687e-03 -1.310762e-03 -1.209833e-03 -1.108902e-03
 [91] -1.007969e-03 -9.070323e-04 -8.060936e-04 -7.051529e-04 -6.042103e-04
 [96] -5.032661e-04 -4.023204e-04 -3.013734e-04 -2.004254e-04 -9.947663e-05
[101]  1.472773e-06  1.024226e-04  2.033725e-04  3.043225e-04  4.052722e-04
[106]  5.062214e-04  6.071699e-04  7.081176e-04  8.090641e-04  9.100093e-04
[111]  1.010953e-03  1.111895e-03  1.212835e-03  1.313773e-03  1.414708e-03
[116]  1.515641e-03  1.616571e-03  1.717497e-03  1.818421e-03  1.919341e-03
[121]  2.020257e-03  2.121170e-03  2.222078e-03  2.322982e-03  2.423882e-03
[126]  2.524776e-03  2.625666e-03  2.726550e-03  2.827429e-03  2.928302e-03
[131]  3.029170e-03  3.130031e-03  3.230886e-03  3.331734e-03  3.432576e-03
[136]  3.533410e-03  3.634237e-03  3.735057e-03  3.835870e-03  3.936674e-03
[141]  4.037470e-03  4.138258e-03  4.239037e-03  4.339808e-03  4.440569e-03
[146]  4.541322e-03  4.642065e-03  4.742798e-03  4.843521e-03  4.944234e-03
[151]  5.044937e-03  5.145629e-03  5.246311e-03  5.346981e-03  5.447640e-03
[156]  5.548288e-03  5.648924e-03  5.749547e-03  5.850159e-03  5.950758e-03
[161]  6.051345e-03  6.151919e-03  6.252480e-03  6.353027e-03  6.453561e-03
[166]  6.554081e-03  6.654587e-03  6.755079e-03  6.855556e-03  6.956018e-03
[171]  7.056466e-03  7.156898e-03  7.257315e-03  7.357716e-03  7.458102e-03
[176]  7.558471e-03  7.658824e-03  7.759160e-03  7.859479e-03  7.959782e-03
[181]  8.060067e-03  8.160334e-03  8.260584e-03  8.360815e-03  8.461029e-03
[186]  8.561224e-03  8.661400e-03  8.761557e-03  8.861694e-03  8.961813e-03
[191]  9.061911e-03  9.161990e-03  9.262048e-03  9.362086e-03  9.462104e-03
[196]  9.562100e-03  9.662075e-03  9.762029e-03  9.861961e-03  9.961871e-03
[201]  1.006176e-02  1.016162e-02  1.026147e-02  1.036129e-02  1.046108e-02
[206]  1.056086e-02  1.066061e-02  1.076033e-02  1.086003e-02  1.095971e-02
[211]  1.105936e-02  1.115899e-02  1.125859e-02  1.135817e-02  1.145772e-02
[216]  1.155725e-02  1.165675e-02  1.175622e-02  1.185567e-02  1.195509e-02
[221]  1.205448e-02  1.215384e-02  1.225318e-02  1.235249e-02  1.245177e-02
[226]  1.255102e-02  1.265024e-02  1.274944e-02  1.284860e-02  1.294774e-02
[231]  1.304685e-02  1.314592e-02  1.324497e-02  1.334398e-02  1.344297e-02
[236]  1.354192e-02  1.364084e-02  1.373973e-02  1.383859e-02  1.393742e-02
[241]  1.403621e-02  1.413497e-02  1.423370e-02  1.433239e-02  1.443105e-02
[246]  1.452968e-02  1.462828e-02  1.472683e-02  1.482536e-02  1.492385e-02
[251]  1.502230e-02  1.512072e-02  1.521911e-02  1.531746e-02  1.541577e-02
[256]  1.551404e-02  1.561228e-02  1.571048e-02  1.580865e-02  1.590678e-02
[261]  1.600486e-02  1.610292e-02  1.620093e-02  1.629890e-02  1.639684e-02
[266]  1.649473e-02  1.659259e-02  1.669041e-02  1.678819e-02  1.688592e-02
[271]  1.698362e-02  1.708127e-02  1.717889e-02  1.727646e-02  1.737399e-02
[276]  1.747148e-02  1.756893e-02  1.766634e-02  1.776370e-02  1.786102e-02
[281]  1.795829e-02  1.805552e-02  1.815271e-02  1.824986e-02  1.834696e-02
[286]  1.844401e-02  1.854102e-02  1.863799e-02  1.873491e-02  1.883178e-02
[291]  1.892861e-02  1.902539e-02  1.912212e-02  1.921881e-02  1.931545e-02
[296]  1.941204e-02  1.950859e-02  1.960508e-02  1.970153e-02  1.979793e-02
[301]  1.989428e-02
> mx
[1] 0.01989428
> mxli
[1] 2
> x1.best
 [1] 1057.5 1921.5 2177.5 1740.0 1681.5 1860.0  840.0  364.0 1681.5 2449.5
[11] 1200.0 1740.0  967.5  647.5 2591.5 1012.0 1567.5 1457.5 1404.0  612.0
[21] 1860.0 1351.5 1104.0 1300.0 1351.5 1984.0 2737.5 1012.0 1300.0 2047.5
[31]  647.5  449.5 1512.0 2047.5  760.0  799.5 1984.0 1012.0 1740.0 1512.0
[41]  799.5 2047.5  364.0  391.5 1012.0 1624.0 1012.0 2380.0 1799.5 1567.5
[51] 1681.5 1249.5 1300.0 1404.0  684.0  241.5 1512.0 2449.5 1921.5 1681.5
[61]  760.0 1200.0 1681.5 1104.0  881.5 1921.5  760.0  799.5 2591.5 2449.5
[71] 1457.5 2112.0
> if (mxli != 0)
+ {
+ if (par1 == 'Full Box-Cox transform') x1 <- (x^mxli - 1) / mxli
+ if (par1 == 'Simple Box-Cox transform') x1 <- x^mxli
+ } else {
+ x1 <- log(x)
+ }
> postscript(file="/var/wessaorg/rcomp/tmp/1ujcw1384975199.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/25xr71384975200.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/3p1vv1384975200.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/42qz61384975200.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/5orv11384975200.ps",horizontal=F,onefile=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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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)
> if(mx<0) {
+ a<-table.row.start(a)
+ a<-table.element(a,'Warning: maximum correlation is negative! The Box-Cox transformation must not be used.',2)
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/6tsa91384975200.tab") 
> if(par5=='Yes') {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Obs.',header=T)
+ a<-table.element(a,'Original',header=T)
+ a<-table.element(a,'Transformed',header=T)
+ a<-table.row.end(a)
+ for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x1.best[i])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/720v51384975200.tab") 
+ }
> 
> try(system("convert tmp/1ujcw1384975199.ps tmp/1ujcw1384975199.png",intern=TRUE))
character(0)
> try(system("convert tmp/25xr71384975200.ps tmp/25xr71384975200.png",intern=TRUE))
character(0)
> try(system("convert tmp/3p1vv1384975200.ps tmp/3p1vv1384975200.png",intern=TRUE))
character(0)
> try(system("convert tmp/42qz61384975200.ps tmp/42qz61384975200.png",intern=TRUE))
character(0)
> try(system("convert tmp/5orv11384975200.ps tmp/5orv11384975200.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.236   0.996   6.216