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)

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.

> x <- c(1.61
+ ,4.28
+ ,3.28
+ ,2.92
+ ,4.61
+ ,3.44
+ ,4.33
+ ,3.61
+ ,4.78
+ ,4.22
+ ,4.44
+ ,4.39
+ ,3.78
+ ,4.44
+ ,2.44
+ ,4.00
+ ,2.94
+ ,3.67
+ ,4.36
+ ,3.06
+ ,3.56
+ ,2.11
+ ,4.67
+ ,3.81
+ ,4.33
+ ,2.89
+ ,3.56
+ ,4.67
+ ,3.61
+ ,4.11
+ ,3.22
+ ,4.00
+ ,4.53
+ ,4.28
+ ,4.50
+ ,2.94
+ ,4.00
+ ,4.28
+ ,3.00
+ ,4.94
+ ,4.56
+ ,4.67
+ ,4.72
+ ,4.39
+ ,3.67
+ ,4.44
+ ,4.61
+ ,4.11
+ ,4.17
+ ,3.61
+ ,4.11
+ ,3.56
+ ,4.11
+ ,4.06
+ ,4.17
+ ,5.00
+ ,4.78
+ ,2.89
+ ,3.89
+ ,4.61
+ ,3.81
+ ,3.56
+ ,3.94
+ ,4.89
+ ,2.89
+ ,4.33
+ ,3.28
+ ,4.11
+ ,3.89
+ ,4.50
+ ,4.56
+ ,3.94
+ ,4.61
+ ,4.06
+ ,3.56
+ ,2.83
+ ,4.33
+ ,4.39
+ ,3.83
+ ,4.44
+ ,3.03
+ ,4.56
+ ,3.28
+ ,3.89
+ ,2.39
+ ,4.72
+ ,3.39
+ ,4.83
+ ,3.28
+ ,4.56
+ ,4.94
+ ,3.78
+ ,4.14
+ ,4.11
+ ,1.89
+ ,2.78
+ ,4.11
+ ,3.81
+ ,3.53
+ ,3.28
+ ,3.67
+ ,4.67
+ ,3.39
+ ,4.33
+ ,2.83
+ ,1.44
+ ,3.50
+ ,4.44
+ ,2.94
+ ,4.17
+ ,3.50
+ ,2.56
+ ,2.56
+ ,3.39
+ ,3.00
+ ,4.44
+ ,4.11
+ ,4.22
+ ,4.78
+ ,4.78
+ ,2.72
+ ,4.22
+ ,4.61
+ ,4.28
+ ,3.22
+ ,4.17
+ ,4.22
+ ,3.92
+ ,4.67
+ ,2.94
+ ,3.28
+ ,4.78
+ ,4.17
+ ,4.61
+ ,4.61
+ ,4.28
+ ,4.50
+ ,4.72
+ ,3.78
+ ,4.56
+ ,4.44
+ ,3.33
+ ,3.94
+ ,4.11
+ ,4.56
+ ,3.50
+ ,4.50
+ ,4.28
+ ,3.94
+ ,3.44
+ ,3.17
+ ,3.67
+ ,4.44
+ ,4.44
+ ,4.39
+ ,3.94
+ ,3.39
+ ,3.61
+ ,2.94
+ ,4.17
+ ,4.83
+ ,4.22
+ ,4.78
+ ,4.33
+ ,3.78
+ ,2.67
+ ,3.78
+ ,4.00
+ ,1.67
+ ,3.61
+ ,3.78
+ ,4.22
+ ,4.72
+ ,3.22
+ ,4.28
+ ,4.78
+ ,3.83
+ ,3.83
+ ,4.50
+ ,4.50
+ ,1.83
+ ,4.72
+ ,3.78
+ ,3.22
+ ,4.44
+ ,3.83
+ ,2.94
+ ,3.83
+ ,3.56
+ ,3.72
+ ,4.00
+ ,4.11
+ ,3.78
+ ,4.67
+ ,3.89
+ ,3.67
+ ,4.50
+ ,4.06
+ ,4.06
+ ,3.11
+ ,4.61
+ ,4.33
+ ,4.44
+ ,4.33
+ ,4.61
+ ,3.56
+ ,4.06
+ ,4.33
+ ,3.83
+ ,4.44
+ ,3.06
+ ,4.94
+ ,4.39
+ ,4.44
+ ,3.33
+ ,4.61
+ ,3.89
+ ,3.50
+ ,4.00
+ ,4.72
+ ,2.83
+ ,3.83
+ ,3.61
+ ,4.39
+ ,3.28
+ ,4.28
+ ,4.28
+ ,4.39
+ ,3.83
+ ,4.67
+ ,4.67
+ ,4.56
+ ,4.14
+ ,3.61
+ ,3.72
+ ,2.89
+ ,3.06
+ ,2.28
+ ,3.72
+ ,4.11
+ ,4.67
+ ,4.78
+ ,4.72
+ ,4.94
+ ,3.83
+ ,3.00
+ ,4.61
+ ,3.22
+ ,2.94
+ ,2.44
+ ,4.78
+ ,3.28
+ ,3.72
+ ,3.67
+ ,3.72
+ ,3.56
+ ,3.67
+ ,4.39
+ ,2.78
+ ,2.50
+ ,4.56
+ ,4.67
+ ,2.89
+ ,4.44
+ ,3.89)
> par5 = 'Yes'
> par4 = '1'
> par3 = '8'
> par2 = '-8'
> par1 = 'Full Box-Cox transform'
> par5 <- 'Yes'
> par4 <- '1'
> par3 <- '8'
> par2 <- '-8'
> 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] 0.080346504 0.080343603 0.080340588 0.080337459 0.080334215 0.080330856
   [7] 0.080327382 0.080323791 0.080320085 0.080316262 0.080312322 0.080308265
  [13] 0.080304090 0.080299797 0.080295386 0.080290856 0.080286206 0.080281437
  [19] 0.080276548 0.080271539 0.080266409 0.080261158 0.080255785 0.080250291
  [25] 0.080244674 0.080238934 0.080233072 0.080227086 0.080220976 0.080214741
  [31] 0.080208383 0.080201899 0.080195289 0.080188554 0.080181693 0.080174705
  [37] 0.080167590 0.080160348 0.080152977 0.080145479 0.080137852 0.080130096
  [43] 0.080122210 0.080114195 0.080106049 0.080097773 0.080089366 0.080080827
  [49] 0.080072156 0.080063353 0.080054418 0.080045349 0.080036147 0.080026810
  [55] 0.080017340 0.080007735 0.079997994 0.079988118 0.079978106 0.079967957
  [61] 0.079957672 0.079947249 0.079936689 0.079925991 0.079915154 0.079904178
  [67] 0.079893062 0.079881807 0.079870412 0.079858876 0.079847199 0.079835381
  [73] 0.079823420 0.079811317 0.079799072 0.079786683 0.079774150 0.079761474
  [79] 0.079748653 0.079735687 0.079722576 0.079709318 0.079695915 0.079682365
  [85] 0.079668668 0.079654823 0.079640830 0.079626689 0.079612399 0.079597960
  [91] 0.079583371 0.079568631 0.079553741 0.079538700 0.079523508 0.079508164
  [97] 0.079492667 0.079477017 0.079461214 0.079445258 0.079429147 0.079412881
 [103] 0.079396461 0.079379885 0.079363153 0.079346265 0.079329219 0.079312017
 [109] 0.079294657 0.079277138 0.079259461 0.079241625 0.079223629 0.079205473
 [115] 0.079187157 0.079168680 0.079150041 0.079131241 0.079112279 0.079093153
 [121] 0.079073865 0.079054413 0.079034796 0.079015016 0.078995070 0.078974958
 [127] 0.078954681 0.078934238 0.078913627 0.078892850 0.078871904 0.078850791
 [133] 0.078829509 0.078808057 0.078786436 0.078764645 0.078742684 0.078720552
 [139] 0.078698248 0.078675772 0.078653124 0.078630303 0.078607309 0.078584141
 [145] 0.078560800 0.078537283 0.078513591 0.078489724 0.078465681 0.078441461
 [151] 0.078417065 0.078392491 0.078367739 0.078342809 0.078317700 0.078292412
 [157] 0.078266944 0.078241296 0.078215467 0.078189458 0.078163267 0.078136893
 [163] 0.078110338 0.078083599 0.078056677 0.078029572 0.078002282 0.077974807
 [169] 0.077947147 0.077919302 0.077891270 0.077863052 0.077834647 0.077806054
 [175] 0.077777274 0.077748305 0.077719147 0.077689800 0.077660263 0.077630536
 [181] 0.077600618 0.077570509 0.077540209 0.077509717 0.077479032 0.077448154
 [187] 0.077417083 0.077385818 0.077354359 0.077322705 0.077290856 0.077258812
 [193] 0.077226571 0.077194134 0.077161500 0.077128669 0.077095640 0.077062413
 [199] 0.077028987 0.076995362 0.076961537 0.076927512 0.076893287 0.076858861
 [205] 0.076824234 0.076789405 0.076754374 0.076719140 0.076683703 0.076648063
 [211] 0.076612219 0.076576171 0.076539918 0.076503459 0.076466796 0.076429926
 [217] 0.076392850 0.076355567 0.076318076 0.076280378 0.076242472 0.076204358
 [223] 0.076166034 0.076127502 0.076088759 0.076049807 0.076010644 0.075971270
 [229] 0.075931684 0.075891887 0.075851878 0.075811656 0.075771222 0.075730574
 [235] 0.075689712 0.075648636 0.075607346 0.075565841 0.075524121 0.075482185
 [241] 0.075440033 0.075397665 0.075355080 0.075312278 0.075269258 0.075226020
 [247] 0.075182565 0.075138890 0.075094997 0.075050885 0.075006552 0.074962000
 [253] 0.074917227 0.074872234 0.074827019 0.074781584 0.074735926 0.074690046
 [259] 0.074643944 0.074597619 0.074551071 0.074504299 0.074457304 0.074410085
 [265] 0.074362641 0.074314973 0.074267079 0.074218960 0.074170616 0.074122045
 [271] 0.074073248 0.074024225 0.073974975 0.073925498 0.073875793 0.073825860
 [277] 0.073775700 0.073725311 0.073674693 0.073623847 0.073572772 0.073521467
 [283] 0.073469932 0.073418168 0.073366174 0.073313949 0.073261493 0.073208806
 [289] 0.073155888 0.073102739 0.073049358 0.072995746 0.072941901 0.072887824
 [295] 0.072833514 0.072778972 0.072724196 0.072669188 0.072613946 0.072558470
 [301] 0.072502761 0.072446817 0.072390640 0.072334228 0.072277582 0.072220701
 [307] 0.072163585 0.072106234 0.072048647 0.071990826 0.071932769 0.071874476
 [313] 0.071815947 0.071757183 0.071698182 0.071638946 0.071579473 0.071519763
 [319] 0.071459817 0.071399634 0.071339215 0.071278558 0.071217665 0.071156534
 [325] 0.071095167 0.071033562 0.070971720 0.070909640 0.070847323 0.070784769
 [331] 0.070721976 0.070658947 0.070595679 0.070532174 0.070468432 0.070404451
 [337] 0.070340233 0.070275777 0.070211083 0.070146151 0.070080981 0.070015574
 [343] 0.069949929 0.069884046 0.069817925 0.069751567 0.069684971 0.069618137
 [349] 0.069551066 0.069483757 0.069416210 0.069348426 0.069280405 0.069212147
 [355] 0.069143651 0.069074918 0.069005948 0.068936742 0.068867298 0.068797618
 [361] 0.068727701 0.068657548 0.068587158 0.068516532 0.068445670 0.068374573
 [367] 0.068303239 0.068231670 0.068159866 0.068087826 0.068015552 0.067943042
 [373] 0.067870298 0.067797320 0.067724107 0.067650660 0.067576980 0.067503066
 [379] 0.067428918 0.067354538 0.067279925 0.067205079 0.067130001 0.067054691
 [385] 0.066979149 0.066903376 0.066827372 0.066751137 0.066674671 0.066597975
 [391] 0.066521050 0.066443894 0.066366510 0.066288896 0.066211055 0.066132985
 [397] 0.066054687 0.065976162 0.065897409 0.065818430 0.065739225 0.065659794
 [403] 0.065580138 0.065500257 0.065420151 0.065339821 0.065259267 0.065178490
 [409] 0.065097490 0.065016268 0.064934824 0.064853158 0.064771272 0.064689165
 [415] 0.064606838 0.064524292 0.064441528 0.064358544 0.064275343 0.064191925
 [421] 0.064108290 0.064024439 0.063940372 0.063856090 0.063771594 0.063686884
 [427] 0.063601961 0.063516825 0.063431477 0.063345917 0.063260147 0.063174166
 [433] 0.063087976 0.063001578 0.062914970 0.062828156 0.062741134 0.062653906
 [439] 0.062566473 0.062478835 0.062390993 0.062302947 0.062214699 0.062126248
 [445] 0.062037597 0.061948745 0.061859693 0.061770442 0.061680993 0.061591346
 [451] 0.061501503 0.061411464 0.061321230 0.061230802 0.061140180 0.061049365
 [457] 0.060958359 0.060867162 0.060775774 0.060684197 0.060592432 0.060500479
 [463] 0.060408340 0.060316014 0.060223504 0.060130810 0.060037932 0.059944872
 [469] 0.059851631 0.059758210 0.059664609 0.059570829 0.059476872 0.059382738
 [475] 0.059288429 0.059193945 0.059099287 0.059004456 0.058909454 0.058814280
 [481] 0.058718937 0.058623426 0.058527746 0.058431900 0.058335888 0.058239711
 [487] 0.058143371 0.058046868 0.057950204 0.057853379 0.057756395 0.057659253
 [493] 0.057561953 0.057464497 0.057366887 0.057269122 0.057171204 0.057073135
 [499] 0.056974915 0.056876546 0.056778029 0.056679364 0.056580553 0.056481597
 [505] 0.056382498 0.056283256 0.056183873 0.056084349 0.055984687 0.055884887
 [511] 0.055784950 0.055684877 0.055584671 0.055484331 0.055383860 0.055283258
 [517] 0.055182527 0.055081668 0.054980681 0.054879569 0.054778333 0.054676974
 [523] 0.054575493 0.054473891 0.054372170 0.054270331 0.054168375 0.054066304
 [529] 0.053964118 0.053861820 0.053759410 0.053656889 0.053554260 0.053451523
 [535] 0.053348680 0.053245732 0.053142680 0.053039525 0.052936270 0.052832915
 [541] 0.052729461 0.052625911 0.052522265 0.052418524 0.052314691 0.052210766
 [547] 0.052106750 0.052002646 0.051898455 0.051794177 0.051689815 0.051585369
 [553] 0.051480841 0.051376233 0.051271545 0.051166780 0.051061938 0.050957022
 [559] 0.050852031 0.050746969 0.050641835 0.050536633 0.050431362 0.050326025
 [565] 0.050220623 0.050115157 0.050009628 0.049904039 0.049798390 0.049692684
 [571] 0.049586920 0.049481102 0.049375230 0.049269305 0.049163330 0.049057305
 [577] 0.048951233 0.048845113 0.048738949 0.048632741 0.048526490 0.048420199
 [583] 0.048313869 0.048207501 0.048101096 0.047994656 0.047888183 0.047781677
 [589] 0.047675141 0.047568576 0.047461983 0.047355364 0.047248719 0.047142052
 [595] 0.047035362 0.046928652 0.046821923 0.046715176 0.046608413 0.046501635
 [601] 0.046394844 0.046288041 0.046181228 0.046074406 0.045967576 0.045860741
 [607] 0.045753900 0.045647057 0.045540212 0.045433366 0.045326522 0.045219680
 [613] 0.045112842 0.045006010 0.044899184 0.044792367 0.044685560 0.044578764
 [619] 0.044471980 0.044365210 0.044258456 0.044151719 0.044045000 0.043938300
 [625] 0.043831622 0.043724966 0.043618334 0.043511728 0.043405148 0.043298596
 [631] 0.043192074 0.043085583 0.042979124 0.042872699 0.042766309 0.042659955
 [637] 0.042553639 0.042447362 0.042341126 0.042234932 0.042128782 0.042022676
 [643] 0.041916615 0.041810603 0.041704639 0.041598725 0.041492863 0.041387053
 [649] 0.041281298 0.041175598 0.041069955 0.040964370 0.040858845 0.040753380
 [655] 0.040647977 0.040542638 0.040437363 0.040332154 0.040227013 0.040121940
 [661] 0.040016937 0.039912005 0.039807146 0.039702360 0.039597649 0.039493014
 [667] 0.039388457 0.039283979 0.039179580 0.039075263 0.038971028 0.038866877
 [673] 0.038762811 0.038658831 0.038554938 0.038451134 0.038347420 0.038243796
 [679] 0.038140265 0.038036827 0.037933484 0.037830236 0.037727085 0.037624032
 [685] 0.037521079 0.037418226 0.037315474 0.037212825 0.037110280 0.037007840
 [691] 0.036905506 0.036803279 0.036701160 0.036599151 0.036497252 0.036395465
 [697] 0.036293791 0.036192230 0.036090784 0.035989454 0.035888242 0.035787147
 [703] 0.035686171 0.035585316 0.035484581 0.035383969 0.035283481 0.035183116
 [709] 0.035082877 0.034982764 0.034882778 0.034782921 0.034683193 0.034583595
 [715] 0.034484129 0.034384794 0.034285593 0.034186526 0.034087594 0.033988798
 [721] 0.033890139 0.033791618 0.033693236 0.033594993 0.033496892 0.033398931
 [727] 0.033301113 0.033203439 0.033105908 0.033008523 0.032911283 0.032814191
 [733] 0.032717246 0.032620449 0.032523802 0.032427305 0.032330959 0.032234765
 [739] 0.032138723 0.032042835 0.031947101 0.031851522 0.031756099 0.031660832
 [745] 0.031565723 0.031470772 0.031375980 0.031281347 0.031186875 0.031092564
 [751] 0.030998414 0.030904427 0.030810604 0.030716944 0.030623449 0.030530119
 [757] 0.030436956 0.030343959 0.030251129 0.030158468 0.030065975 0.029973652
 [763] 0.029881499 0.029789516 0.029697704 0.029606065 0.029514598 0.029423304
 [769] 0.029332184 0.029241238 0.029150467 0.029059871 0.028969452 0.028879209
 [775] 0.028789144 0.028699256 0.028609546 0.028520016 0.028430665 0.028341493
 [781] 0.028252502 0.028163692 0.028075064 0.027986617 0.027898353 0.027810271
 [787] 0.027722374 0.027634660 0.027547130 0.027459785 0.027372626 0.027285652
 [793] 0.027198864 0.027112263 0.027025849 0.026939622 0.026853583 0.026767733
 [799] 0.026682071 0.026596598 0.026511314 0.026426221 0.026341317 0.026256604
 [805] 0.026172082 0.026087751 0.026003612 0.025919665 0.025835911 0.025752348
 [811] 0.025668979 0.025585803 0.025502821 0.025420033 0.025337439 0.025255039
 [817] 0.025172834 0.025090825 0.025009010 0.024927391 0.024845968 0.024764742
 [823] 0.024683711 0.024602878 0.024522241 0.024441801 0.024361559 0.024281514
 [829] 0.024201667 0.024122018 0.024042567 0.023963315 0.023884261 0.023805406
 [835] 0.023726750 0.023648294 0.023570036 0.023491978 0.023414120 0.023336461
 [841] 0.023259003 0.023181744 0.023104686 0.023027828 0.022951171 0.022874714
 [847] 0.022798459 0.022722403 0.022646549 0.022570897 0.022495445 0.022420194
 [853] 0.022345145 0.022270297 0.022195651 0.022121207 0.022046964 0.021972922
 [859] 0.021899083 0.021825446 0.021752010 0.021678776 0.021605744 0.021532914
 [865] 0.021460287 0.021387861 0.021315637 0.021243616 0.021171796 0.021100179
 [871] 0.021028764 0.020957551 0.020886540 0.020815731 0.020745124 0.020674719
 [877] 0.020604516 0.020534516 0.020464717 0.020395120 0.020325725 0.020256532
 [883] 0.020187540 0.020118751 0.020050163 0.019981776 0.019913592 0.019845608
 [889] 0.019777826 0.019710246 0.019642866 0.019575688 0.019508711 0.019441935
 [895] 0.019375359 0.019308985 0.019242811 0.019176838 0.019111065 0.019045492
 [901] 0.018980120 0.018914948 0.018849976 0.018785203 0.018720630 0.018656257
 [907] 0.018592083 0.018528109 0.018464334 0.018400757 0.018337380 0.018274201
 [913] 0.018211220 0.018148438 0.018085854 0.018023468 0.017961280 0.017899290
 [919] 0.017837497 0.017775901 0.017714503 0.017653301 0.017592296 0.017531488
 [925] 0.017470876 0.017410460 0.017350240 0.017290215 0.017230387 0.017170753
 [931] 0.017111315 0.017052071 0.016993022 0.016934168 0.016875508 0.016817041
 [937] 0.016758769 0.016700690 0.016642804 0.016585111 0.016527612 0.016470304
 [943] 0.016413189 0.016356266 0.016299535 0.016242995 0.016186647 0.016130490
 [949] 0.016074524 0.016018748 0.015963162 0.015907766 0.015852560 0.015797544
 [955] 0.015742717 0.015688078 0.015633629 0.015579367 0.015525294 0.015471409
 [961] 0.015417711 0.015364200 0.015310876 0.015257739 0.015204788 0.015152024
 [967] 0.015099445 0.015047051 0.014994843 0.014942820 0.014890981 0.014839326
 [973] 0.014787856 0.014736569 0.014685465 0.014634545 0.014583807 0.014533251
 [979] 0.014482878 0.014432687 0.014382677 0.014332848 0.014283200 0.014233732
 [985] 0.014184444 0.014135337 0.014086409 0.014037660 0.013989090 0.013940698
 [991] 0.013892485 0.013844450 0.013796592 0.013748911 0.013701407 0.013654080
 [997] 0.013606929 0.013559954 0.013513154 0.013466529 0.013420079 0.013373804
[1003] 0.013327703 0.013281775 0.013236021 0.013190440 0.013145032 0.013099796
[1009] 0.013054732 0.013009840 0.012965119 0.012920569 0.012876190 0.012831981
[1015] 0.012787942 0.012744072 0.012700372 0.012656840 0.012613477 0.012570282
[1021] 0.012527254 0.012484394 0.012441701 0.012399175 0.012356815 0.012314621
[1027] 0.012272592 0.012230729 0.012189030 0.012147496 0.012106126 0.012064920
[1033] 0.012023877 0.011982996 0.011942279 0.011901724 0.011861330 0.011821098
[1039] 0.011781027 0.011741117 0.011701368 0.011661778 0.011622348 0.011583077
[1045] 0.011543965 0.011505011 0.011466216 0.011427578 0.011389098 0.011350775
[1051] 0.011312608 0.011274597 0.011236743 0.011199043 0.011161499 0.011124110
[1057] 0.011086875 0.011049794 0.011012867 0.010976092 0.010939471 0.010903002
[1063] 0.010866685 0.010830520 0.010794506 0.010758643 0.010722930 0.010687368
[1069] 0.010651955 0.010616692 0.010581578 0.010546613 0.010511796 0.010477126
[1075] 0.010442604 0.010408230 0.010374002 0.010339920 0.010305985 0.010272195
[1081] 0.010238550 0.010205050 0.010171695 0.010138483 0.010105415 0.010072491
[1087] 0.010039710 0.010007071 0.009974574 0.009942219 0.009910006 0.009877933
[1093] 0.009846002 0.009814210 0.009782559 0.009751047 0.009719674 0.009688440
[1099] 0.009657344 0.009626386 0.009595566 0.009564883 0.009534337 0.009503928
[1105] 0.009473655 0.009443517 0.009413515 0.009383648 0.009353915 0.009324317
[1111] 0.009294853 0.009265522 0.009236324 0.009207259 0.009178326 0.009149525
[1117] 0.009120856 0.009092319 0.009063912 0.009035635 0.009007489 0.008979473
[1123] 0.008951586 0.008923828 0.008896198 0.008868697 0.008841324 0.008814078
[1129] 0.008786960 0.008759968 0.008733103 0.008706364 0.008679751 0.008653263
[1135] 0.008626900 0.008600661 0.008574547 0.008548557 0.008522690 0.008496947
[1141] 0.008471326 0.008445827 0.008420451 0.008395196 0.008370063 0.008345051
[1147] 0.008320159 0.008295388 0.008270736 0.008246204 0.008221792 0.008197498
[1153] 0.008173322 0.008149265 0.008125325 0.008101503 0.008077798 0.008054210
[1159] 0.008030738 0.008007382 0.007984141 0.007961016 0.007938006 0.007915110
[1165] 0.007892329 0.007869661 0.007847107 0.007824666 0.007802338 0.007780123
[1171] 0.007758019 0.007736028 0.007714148 0.007692379 0.007670720 0.007649172
[1177] 0.007627735 0.007606406 0.007585188 0.007564078 0.007543077 0.007522185
[1183] 0.007501400 0.007480723 0.007460154 0.007439691 0.007419335 0.007399086
[1189] 0.007378942 0.007358904 0.007338971 0.007319144 0.007299421 0.007279802
[1195] 0.007260288 0.007240877 0.007221569 0.007202365 0.007183263 0.007164263
[1201] 0.007145365 0.007126569 0.007107875 0.007089281 0.007070789 0.007052396
[1207] 0.007034104 0.007015911 0.006997818 0.006979824 0.006961928 0.006944131
[1213] 0.006926433 0.006908832 0.006891328 0.006873922 0.006856612 0.006839400
[1219] 0.006822283 0.006805262 0.006788337 0.006771507 0.006754772 0.006738132
[1225] 0.006721586 0.006705134 0.006688776 0.006672511 0.006656339 0.006640260
[1231] 0.006624274 0.006608379 0.006592577 0.006576866 0.006561247 0.006545718
[1237] 0.006530280 0.006514933 0.006499675 0.006484507 0.006469429 0.006454440
[1243] 0.006439539 0.006424728 0.006410004 0.006395369 0.006380821 0.006366360
[1249] 0.006351987 0.006337700 0.006323500 0.006309386 0.006295358 0.006281415
[1255] 0.006267558 0.006253786 0.006240098 0.006226495 0.006212976 0.006199541
[1261] 0.006186190 0.006172922 0.006159737 0.006146635 0.006133615 0.006120677
[1267] 0.006107821 0.006095047 0.006082354 0.006069742 0.006057211 0.006044761
[1273] 0.006032390 0.006020100 0.006007889 0.005995757 0.005983705 0.005971732
[1279] 0.005959837 0.005948020 0.005936281 0.005924620 0.005913037 0.005901531
[1285] 0.005890101 0.005878749 0.005867472 0.005856272 0.005845148 0.005834099
[1291] 0.005823126 0.005812227 0.005801404 0.005790655 0.005779980 0.005769380
[1297] 0.005758853 0.005748399 0.005738019 0.005727712 0.005717477 0.005707315
[1303] 0.005697225 0.005687207 0.005677261 0.005667386 0.005657583 0.005647850
[1309] 0.005638188 0.005628596 0.005619075 0.005609623 0.005600241 0.005590929
[1315] 0.005581686 0.005572511 0.005563406 0.005554369 0.005545400 0.005536499
[1321] 0.005527665 0.005518899 0.005510201 0.005501569 0.005493004 0.005484505
[1327] 0.005476073 0.005467707 0.005459406 0.005451171 0.005443002 0.005434897
[1333] 0.005426857 0.005418882 0.005410971 0.005403124 0.005395341 0.005387622
[1339] 0.005379966 0.005372374 0.005364844 0.005357377 0.005349972 0.005342630
[1345] 0.005335350 0.005328132 0.005320975 0.005313879 0.005306845 0.005299872
[1351] 0.005292959 0.005286107 0.005279315 0.005272583 0.005265910 0.005259298
[1357] 0.005252744 0.005246250 0.005239815 0.005233438 0.005227120 0.005220860
[1363] 0.005214658 0.005208514 0.005202428 0.005196398 0.005190427 0.005184512
[1369] 0.005178653 0.005172852 0.005167106 0.005161417 0.005155784 0.005150206
[1375] 0.005144684 0.005139217 0.005133805 0.005128448 0.005123146 0.005117898
[1381] 0.005112705 0.005107565 0.005102479 0.005097447 0.005092468 0.005087543
[1387] 0.005082670 0.005077851 0.005073084 0.005068369 0.005063707 0.005059096
[1393] 0.005054538 0.005050031 0.005045575 0.005041171 0.005036818 0.005032515
[1399] 0.005028263 0.005024062 0.005019911 0.005015810 0.005011759 0.005007757
[1405] 0.005003805 0.004999902 0.004996049 0.004992244 0.004988488 0.004984780
[1411] 0.004981121 0.004977510 0.004973947 0.004970432 0.004966965 0.004963544
[1417] 0.004960172 0.004956846 0.004953567 0.004950334 0.004947148 0.004944009
[1423] 0.004940915 0.004937868 0.004934866 0.004931910 0.004929000 0.004926134
[1429] 0.004923314 0.004920538 0.004917807 0.004915121 0.004912479 0.004909882
[1435] 0.004907328 0.004904818 0.004902352 0.004899929 0.004897549 0.004895213
[1441] 0.004892920 0.004890669 0.004888461 0.004886296 0.004884173 0.004882092
[1447] 0.004880052 0.004878055 0.004876099 0.004874185 0.004872312 0.004870480
[1453] 0.004868689 0.004866939 0.004865230 0.004863560 0.004861932 0.004860343
[1459] 0.004858794 0.004857285 0.004855816 0.004854386 0.004852996 0.004851645
[1465] 0.004850332 0.004849059 0.004847824 0.004846628 0.004845470 0.004844351
[1471] 0.004843269 0.004842225 0.004841219 0.004840251 0.004839320 0.004838427
[1477] 0.004837570 0.004836751 0.004835968 0.004835222 0.004834512 0.004833839
[1483] 0.004833202 0.004832602 0.004832037 0.004831507 0.004831014 0.004830556
[1489] 0.004830133 0.004829746 0.004829393 0.004829076 0.004828793 0.004828544
[1495] 0.004828331 0.004828151 0.004828006 0.004827894 0.004827817 0.004827773
[1501] 0.004827763 0.004827786 0.004827843 0.004827932 0.004828055 0.004828211
[1507] 0.004828399 0.004828620 0.004828874 0.004829159 0.004829477 0.004829827
[1513] 0.004830209 0.004830623 0.004831068 0.004831545 0.004832054 0.004832593
[1519] 0.004833164 0.004833765 0.004834397 0.004835060 0.004835754 0.004836478
[1525] 0.004837232 0.004838017 0.004838832 0.004839676 0.004840550 0.004841454
[1531] 0.004842388 0.004843350 0.004844342 0.004845364 0.004846414 0.004847493
[1537] 0.004848601 0.004849737 0.004850902 0.004852095 0.004853317 0.004854566
[1543] 0.004855844 0.004857150 0.004858483 0.004859844 0.004861232 0.004862648
[1549] 0.004864091 0.004865561 0.004867058 0.004868582 0.004870133 0.004871710
[1555] 0.004873314 0.004874945 0.004876601 0.004878284 0.004879993 0.004881728
[1561] 0.004883489 0.004885275 0.004887087 0.004888924 0.004890787 0.004892675
[1567] 0.004894588 0.004896526 0.004898489 0.004900476 0.004902489 0.004904526
[1573] 0.004906587 0.004908673 0.004910782 0.004912916 0.004915074 0.004917256
[1579] 0.004919461 0.004921691 0.004923943 0.004926219 0.004928519 0.004930841
[1585] 0.004933187 0.004935556 0.004937947 0.004940362 0.004942799 0.004945258
[1591] 0.004947740 0.004950245 0.004952771 0.004955320 0.004957890 0.004960483
[1597] 0.004963097 0.004965734 0.004968391 0.004971070 0.004973771
> mx
[1] 0.0803465
> mxli
[1] -8
> x1.best
  [1] 0.1249420 0.1249998 0.1249989 0.1249978 0.1249999 0.1249992 0.1249998
  [8] 0.1249994 0.1249999 0.1249998 0.1249998 0.1249998 0.1249995 0.1249998
 [15] 0.1249936 0.1249997 0.1249978 0.1249994 0.1249998 0.1249983 0.1249993
 [22] 0.1249857 0.1249999 0.1249996 0.1249998 0.1249976 0.1249993 0.1249999
 [29] 0.1249994 0.1249997 0.1249988 0.1249997 0.1249999 0.1249998 0.1249999
 [36] 0.1249978 0.1249997 0.1249998 0.1249981 0.1249999 0.1249999 0.1249999
 [43] 0.1249999 0.1249998 0.1249994 0.1249998 0.1249999 0.1249997 0.1249998
 [50] 0.1249994 0.1249997 0.1249993 0.1249997 0.1249997 0.1249998 0.1249999
 [57] 0.1249999 0.1249976 0.1249996 0.1249999 0.1249996 0.1249993 0.1249996
 [64] 0.1249999 0.1249976 0.1249998 0.1249989 0.1249997 0.1249996 0.1249999
 [71] 0.1249999 0.1249996 0.1249999 0.1249997 0.1249993 0.1249973 0.1249998
 [78] 0.1249998 0.1249996 0.1249998 0.1249982 0.1249999 0.1249989 0.1249996
 [85] 0.1249928 0.1249999 0.1249991 0.1249999 0.1249989 0.1249999 0.1249999
 [92] 0.1249995 0.1249997 0.1249997 0.1249743 0.1249970 0.1249997 0.1249996
 [99] 0.1249993 0.1249989 0.1249994 0.1249999 0.1249991 0.1249998 0.1249973
[106] 0.1249005 0.1249993 0.1249998 0.1249978 0.1249998 0.1249993 0.1249952
[113] 0.1249952 0.1249991 0.1249981 0.1249998 0.1249997 0.1249998 0.1249999
[120] 0.1249999 0.1249966 0.1249998 0.1249999 0.1249998 0.1249988 0.1249998
[127] 0.1249998 0.1249996 0.1249999 0.1249978 0.1249989 0.1249999 0.1249998
[134] 0.1249999 0.1249999 0.1249998 0.1249999 0.1249999 0.1249995 0.1249999
[141] 0.1249998 0.1249990 0.1249996 0.1249997 0.1249999 0.1249993 0.1249999
[148] 0.1249998 0.1249996 0.1249992 0.1249986 0.1249994 0.1249998 0.1249998
[155] 0.1249998 0.1249996 0.1249991 0.1249994 0.1249978 0.1249998 0.1249999
[162] 0.1249998 0.1249999 0.1249998 0.1249995 0.1249962 0.1249995 0.1249997
[169] 0.1249516 0.1249994 0.1249995 0.1249998 0.1249999 0.1249988 0.1249998
[176] 0.1249999 0.1249996 0.1249996 0.1249999 0.1249999 0.1249696 0.1249999
[183] 0.1249995 0.1249988 0.1249998 0.1249996 0.1249978 0.1249996 0.1249993
[190] 0.1249995 0.1249997 0.1249997 0.1249995 0.1249999 0.1249996 0.1249994
[197] 0.1249999 0.1249997 0.1249997 0.1249985 0.1249999 0.1249998 0.1249998
[204] 0.1249998 0.1249999 0.1249993 0.1249997 0.1249998 0.1249996 0.1249998
[211] 0.1249983 0.1249999 0.1249998 0.1249998 0.1249990 0.1249999 0.1249996
[218] 0.1249993 0.1249997 0.1249999 0.1249973 0.1249996 0.1249994 0.1249998
[225] 0.1249989 0.1249998 0.1249998 0.1249998 0.1249996 0.1249999 0.1249999
[232] 0.1249999 0.1249997 0.1249994 0.1249995 0.1249976 0.1249983 0.1249907
[239] 0.1249995 0.1249997 0.1249999 0.1249999 0.1249999 0.1249999 0.1249996
[246] 0.1249981 0.1249999 0.1249988 0.1249978 0.1249936 0.1249999 0.1249989
[253] 0.1249995 0.1249994 0.1249995 0.1249993 0.1249994 0.1249998 0.1249970
[260] 0.1249944 0.1249999 0.1249999 0.1249976 0.1249998 0.1249996
> 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/1quor1393223136.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/2ubfg1393223136.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/3ppat1393223136.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/4j9sh1393223136.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/5m6nk1393223136.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/6jhl61393223136.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/7apmc1393223136.tab") 
+ }
> 
> try(system("convert tmp/1quor1393223136.ps tmp/1quor1393223136.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ubfg1393223136.ps tmp/2ubfg1393223136.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ppat1393223136.ps tmp/3ppat1393223136.png",intern=TRUE))
character(0)
> try(system("convert tmp/4j9sh1393223136.ps tmp/4j9sh1393223136.png",intern=TRUE))
character(0)
> try(system("convert tmp/5m6nk1393223136.ps tmp/5m6nk1393223136.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.875   0.999   6.885