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Data:
28.8 2381.7 1246.7 2780.4 29.7 7741.2 83.9 86.6 13.9 0.8 147.6 0.4 207.6 30.5 23 114.8 38.4 1098.6 51.2 581.7 8515.8 5.8 111 274.2 181 4 756.1 9562.9 1.1 0.035 1141.7 2344.9 51.1 322.5 56.6 9.3 78.9 48.7 1001.5 45.2 18.3 338.4 549.1 69.7 357.4 132 108.9 36.1 215 27.8 112.5 93 1910.9 22.1 301.3 11 378 89.3 580.4 100.3 199.9 64.5 10.5 30.4 111.4 25.7 330.8 0.3 1240.2 0.3 2 1964.4 33.9 1564.1 13.8 799.4 676.6 824.3 267.7 130.4 1267 0.5 75.4 406.8 1285.2 300 312.7 11.6 238.4 17098.3 26.3 2149.7 196.7 0.459 72.3 49 20.3 505.9 1879.4 163.8 447.4 141.4 947.3 513.1 56.8 0.8 0.026 241.6 9831.5 447.4 6
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R Code
par3 <- '0.05' par2 <- '0.95' par1 <- '0.05' par1 <- as(par1,'numeric') par2 <- as(par2,'numeric') par3 <- as(par3,'numeric') library(Hmisc) myseq <- seq(par1, par2, par3) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) bitmap(file='test1.png') plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'quantiles',header=TRUE) a<-table.element(a,'value',header=TRUE) a<-table.element(a,'standard error',header=TRUE) a<-table.row.end(a) length(hd) for (i in 1:length(hd)) { a<-table.row.start(a) a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE) a<-table.element(a,signif(as.matrix(hd[i])[1,1],6)) a<-table.element(a,signif(as.matrix(attr(hd,'se')[i])[1,1],6)) 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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