R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > y <- c(0.3,2.1,2.5,2.3,2.4,3,1.7,3.5,4,3.7,3.7,3,2.7,2.5,2.2,2.9,3.1,3,2.8,2.5,1.9,1.9,1.8,2,2.6,2.5,2.5,1.6,1.4,0.8,1.1,1.3,1.2,1.3,1.1,1.3,1.2,1.6,1.7,1.5,0.9,1.5,1.4,1.6,1.7,1.4,1.8,1.7,1.4,1.2,1,1.7,2.4,2,2.1,2,1.8,2.7,2.3,1.9,2,2.3,2.8,2.4,2.3,2.7,2.7,2.9,3,2.2,2.3,2.8) > x <- c(1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.44,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.57,1.58,1.58,1.58,1.58,1.59,1.6,1.6,1.61,1.61,1.61,1.62,1.63,1.63,1.64,1.64,1.64,1.64,1.64,1.65,1.65,1.65,1.65) > #'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] -1.044066e-02 -1.032327e-02 -1.020590e-02 -1.008854e-02 -9.971194e-03 [6] -9.853867e-03 -9.736556e-03 -9.619260e-03 -9.501981e-03 -9.384718e-03 [11] -9.267470e-03 -9.150239e-03 -9.033024e-03 -8.915824e-03 -8.798641e-03 [16] -8.681474e-03 -8.564323e-03 -8.447188e-03 -8.330069e-03 -8.212967e-03 [21] -8.095880e-03 -7.978810e-03 -7.861756e-03 -7.744719e-03 -7.627698e-03 [26] -7.510693e-03 -7.393704e-03 -7.276732e-03 -7.159776e-03 -7.042837e-03 [31] -6.925914e-03 -6.809008e-03 -6.692118e-03 -6.575245e-03 -6.458388e-03 [36] -6.341548e-03 -6.224724e-03 -6.107917e-03 -5.991127e-03 -5.874353e-03 [41] -5.757596e-03 -5.640856e-03 -5.524132e-03 -5.407426e-03 -5.290736e-03 [46] -5.174063e-03 -5.057406e-03 -4.940767e-03 -4.824145e-03 -4.707539e-03 [51] -4.590950e-03 -4.474379e-03 -4.357824e-03 -4.241286e-03 -4.124766e-03 [56] -4.008262e-03 -3.891776e-03 -3.775306e-03 -3.658854e-03 -3.542419e-03 [61] -3.426001e-03 -3.309600e-03 -3.193217e-03 -3.076850e-03 -2.960501e-03 [66] -2.844169e-03 -2.727855e-03 -2.611558e-03 -2.495278e-03 -2.379016e-03 [71] -2.262771e-03 -2.146544e-03 -2.030334e-03 -1.914141e-03 -1.797966e-03 [76] -1.681809e-03 -1.565669e-03 -1.449546e-03 -1.333441e-03 -1.217354e-03 [81] -1.101285e-03 -9.852330e-04 -8.691989e-04 -7.531825e-04 -6.371838e-04 [86] -5.212028e-04 -4.052397e-04 -2.892944e-04 -1.733669e-04 -5.745725e-05 [91] 5.843452e-05 1.743084e-04 2.901643e-04 4.060023e-04 5.218223e-04 [96] 6.376243e-04 7.534083e-04 8.691743e-04 9.849222e-04 1.100652e-03 [101] 1.216364e-03 1.332057e-03 1.447733e-03 1.563390e-03 1.679029e-03 [106] 1.794650e-03 1.910252e-03 2.025837e-03 2.141403e-03 2.256950e-03 [111] 2.372480e-03 2.487991e-03 2.603483e-03 2.718957e-03 2.834413e-03 [116] 2.949850e-03 3.065269e-03 3.180670e-03 3.296051e-03 3.411415e-03 [121] 3.526759e-03 3.642085e-03 3.757393e-03 3.872682e-03 3.987952e-03 [126] 4.103204e-03 4.218436e-03 4.333650e-03 4.448846e-03 4.564022e-03 [131] 4.679180e-03 4.794319e-03 4.909439e-03 5.024540e-03 5.139623e-03 [136] 5.254686e-03 5.369731e-03 5.484756e-03 5.599763e-03 5.714751e-03 [141] 5.829719e-03 5.944669e-03 6.059599e-03 6.174511e-03 6.289403e-03 [146] 6.404276e-03 6.519130e-03 6.633965e-03 6.748781e-03 6.863577e-03 [151] 6.978354e-03 7.093112e-03 7.207851e-03 7.322570e-03 7.437270e-03 [156] 7.551951e-03 7.666612e-03 7.781254e-03 7.895876e-03 8.010479e-03 [161] 8.125063e-03 8.239627e-03 8.354171e-03 8.468696e-03 8.583202e-03 [166] 8.697688e-03 8.812154e-03 8.926601e-03 9.041028e-03 9.155435e-03 [171] 9.269823e-03 9.384191e-03 9.498539e-03 9.612868e-03 9.727176e-03 [176] 9.841465e-03 9.955735e-03 1.006998e-02 1.018421e-02 1.029842e-02 [181] 1.041261e-02 1.052678e-02 1.064093e-02 1.075506e-02 1.086917e-02 [186] 1.098326e-02 1.109733e-02 1.121138e-02 1.132541e-02 1.143942e-02 [191] 1.155341e-02 1.166738e-02 1.178133e-02 1.189526e-02 1.200917e-02 [196] 1.212305e-02 1.223692e-02 1.235077e-02 1.246460e-02 1.257841e-02 [201] 1.269219e-02 1.280596e-02 1.291971e-02 1.303343e-02 1.314714e-02 [206] 1.326082e-02 1.337449e-02 1.348813e-02 1.360176e-02 1.371536e-02 [211] 1.382894e-02 1.394250e-02 1.405605e-02 1.416957e-02 1.428307e-02 [216] 1.439655e-02 1.451001e-02 1.462344e-02 1.473686e-02 1.485026e-02 [221] 1.496363e-02 1.507699e-02 1.519032e-02 1.530364e-02 1.541693e-02 [226] 1.553020e-02 1.564345e-02 1.575668e-02 1.586989e-02 1.598308e-02 [231] 1.609625e-02 1.620939e-02 1.632252e-02 1.643562e-02 1.654871e-02 [236] 1.666177e-02 1.677481e-02 1.688783e-02 1.700083e-02 1.711381e-02 [241] 1.722676e-02 1.733970e-02 1.745261e-02 1.756551e-02 1.767838e-02 [246] 1.779123e-02 1.790406e-02 1.801687e-02 1.812965e-02 1.824242e-02 [251] 1.835516e-02 1.846788e-02 1.858058e-02 1.869326e-02 1.880592e-02 [256] 1.891856e-02 1.903117e-02 1.914377e-02 1.925634e-02 1.936889e-02 [261] 1.948142e-02 1.959393e-02 1.970641e-02 1.981888e-02 1.993132e-02 [266] 2.004374e-02 2.015614e-02 2.026851e-02 2.038087e-02 2.049320e-02 [271] 2.060552e-02 2.071781e-02 2.083007e-02 2.094232e-02 2.105454e-02 [276] 2.116675e-02 2.127893e-02 2.139109e-02 2.150322e-02 2.161534e-02 [281] 2.172743e-02 2.183950e-02 2.195155e-02 2.206358e-02 2.217558e-02 [286] 2.228757e-02 2.239953e-02 2.251147e-02 2.262338e-02 2.273528e-02 [291] 2.284715e-02 2.295900e-02 2.307083e-02 2.318263e-02 2.329441e-02 [296] 2.340618e-02 2.351791e-02 2.362963e-02 2.374132e-02 2.385300e-02 [301] 2.396465e-02 2.407627e-02 2.418788e-02 2.429946e-02 2.441102e-02 [306] 2.452255e-02 2.463407e-02 2.474556e-02 2.485703e-02 2.496848e-02 [311] 2.507990e-02 2.519130e-02 2.530268e-02 2.541404e-02 2.552537e-02 [316] 2.563668e-02 2.574797e-02 2.585924e-02 2.597048e-02 2.608170e-02 [321] 2.619290e-02 2.630407e-02 2.641523e-02 2.652636e-02 2.663746e-02 [326] 2.674855e-02 2.685961e-02 2.697064e-02 2.708166e-02 2.719265e-02 [331] 2.730362e-02 2.741457e-02 2.752549e-02 2.763639e-02 2.774727e-02 [336] 2.785812e-02 2.796895e-02 2.807976e-02 2.819054e-02 2.830130e-02 [341] 2.841204e-02 2.852276e-02 2.863345e-02 2.874412e-02 2.885476e-02 [346] 2.896539e-02 2.907598e-02 2.918656e-02 2.929711e-02 2.940764e-02 [351] 2.951815e-02 2.962863e-02 2.973909e-02 2.984953e-02 2.995994e-02 [356] 3.007033e-02 3.018069e-02 3.029103e-02 3.040135e-02 3.051165e-02 [361] 3.062192e-02 3.073217e-02 3.084239e-02 3.095259e-02 3.106277e-02 [366] 3.117292e-02 3.128305e-02 3.139316e-02 3.150324e-02 3.161330e-02 [371] 3.172334e-02 3.183335e-02 3.194334e-02 3.205330e-02 3.216324e-02 [376] 3.227316e-02 3.238305e-02 3.249292e-02 3.260277e-02 3.271259e-02 [381] 3.282238e-02 3.293216e-02 3.304191e-02 3.315163e-02 3.326133e-02 [386] 3.337101e-02 3.348067e-02 3.359030e-02 3.369990e-02 3.380948e-02 [391] 3.391904e-02 3.402857e-02 3.413808e-02 3.424757e-02 3.435703e-02 [396] 3.446647e-02 3.457588e-02 3.468527e-02 3.479463e-02 3.490397e-02 [401] 3.501329e-02 > mx [1] 0.03501329 > 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/19ae01258033307.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/2nb811258033307.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/3djjo1258033307.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/43o231258033307.tab") > > system("convert tmp/19ae01258033307.ps tmp/19ae01258033307.png") > system("convert tmp/2nb811258033307.ps tmp/2nb811258033307.png") > system("convert tmp/3djjo1258033307.ps tmp/3djjo1258033307.png") > > > proc.time() user system elapsed 0.783 0.503 1.004