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Data:
150.790688775846 -6258.83534189665 1179.70002837875 12383.4735350986 6452.27270900916 17925.4944763725 9257.68433920925 -11723.3498644816 9730.29130029668 1936.54617702668 -13491.8770530529 -13575.4890229713 16045.3501201983 31348.045275449 7731.3341195073 22856.4486960203 9073.2631337878 9741.59405237557 1332.23572230402 -4628.33356110052 -4607.73974806942 10468.3136697059 3481.88214736408 25028.6738442344 43679.0460797915 3133.96300715266 49119.3221578365 -29338.6167794636 -34798.4849473318 -18302.9667882799 -11186.9532031470 -30966.7969435158 7455.0861209843 8399.08769635226 -7128.66714707987 -710.3526687469 38360.0693181986 -86558.4287678845 -14187.9571747546 3452.42288668084 -5961.29547826464 10305.4208935305 17920.5309412364 1516.14971428292 160300.016991544 12283.5231099274 -7608.94694452296 -8111.9760189687 -51104.480478478 14051.3976851153 -26934.501973342 8297.05855141608 7997.75560146061 -11323.2347058055 -29104.6052892639 -8804.79506817229 -36655.7461215054 -21480.2013942902 22717.8851070332 -49675.4810209872 -43007.5042557363 17078.2355867197 -31075.4428611256 20753.5566469650 -866.61457864198 12546.4353825002 53033.941150139 11101.0470118611 -27479.2194387895 -22585.9201086563 17607.2507747408 326551.315645887 -14702.2973393577 29501.4682467813 30906.0918468706 -11697.8693797096 19443.5659647436 9599.18339880255 3414.58835532525 24385.1665443376 -55436.4896111982 24357.0626776376 9597.46988149706 -71563.4063280716 6914.44503835373 12057.6240025949 -8581.25723332376 -23608.2928407493 -30894.6657060471 -6201.06970316944 -18465.4746948189 -18944.3321613762 16396.3058775606 -545.771753456022 -34797.1597979204 -61904.9006746859 -20410.1549297337 9854.80042974788 1357.59845540812 -22560.9540910830 -12724.6492980212 1756.58704714364 -7765.37726810927 -10338.4454327962 -19622.9718791054
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R Code
gp <- function(lambda, p) { (p^lambda-(1-p)^lambda)/lambda } sortx <- sort(x) c <- array(NA,dim=c(201)) for (i in 1:201) { if (i != 101) c[i] <- cor(gp(ppoints(x), lambda=(i-101)/100),sortx) } bitmap(file='test1.png') plot((-100:100)/100,c[1:201],xlab='lambda',ylab='correlation',main='PPCC Plot - Tukey lambda') grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Tukey Lambda - Key Values',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Distribution (lambda)',1,TRUE) a<-table.element(a,'Correlation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Approx. Cauchy (lambda=-1)',header=TRUE) a<-table.element(a,c[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Exact Logistic (lambda=0)',header=TRUE) a<-table.element(a,(c[100]+c[102])/2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Approx. Normal (lambda=0.14)',header=TRUE) a<-table.element(a,c[115]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'U-shaped (lambda=0.5)',header=TRUE) a<-table.element(a,c[151]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Exactly Uniform (lambda=1)',header=TRUE) a<-table.element(a,c[201]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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