Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
-0.385868851153837 4.81234262686034 -5.86804122114596 16.0725680225492 -8.57525163788969 5.08247518971098 0.092732021505415 3.83298655010795 5.81986266263392 37.1247698411582 -0.456916305824569 -3.62813490741323 -3.87648507892191 4.61958462101272 -12.967748044016 3.19886759717217 -5.74783565702396 -0.568909646003526 -7.15658094463292 -18.0497313555278 15.6314099338156 -18.6819481453537 -0.704909311621681 2.59171945848611 2.56763423323193 0.363060127151921 32.5587282582796 8.52568321864334 1.42269516052334 3.53469472344553 0.904411865388995 -1.1005444418027 13.3248076718110 -33.5907843348750 -0.845486516554237 42.0892768528428 -6.25360506437205 -11.0785340316643 -29.2902232669615 -11.1727173982373 13.9239510644368 13.5369579913798 -16.4941540115674 -9.38355957013267 -2.83541693438183 -2.88173330956316 6.18397479401454 3.71189006095175 3.17508248559435 -4.18249526402528 13.6042900329871 4.81933405297545 10.0482983006261 9.69015652302726 -13.6259654676286 2.81390485024080 2.39082408194279 9.1175078099302 14.2141474796521 3.49385172983141 5.51425675339953 -6.1504957612917 2.72297593670155 -11.1163190852539 -4.69675096946234 1.81576665288666 -10.4353591925503 6.036622781552
Chart options
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')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation