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Data:
196.09 192.64 189.19 182.29 252.11 248.66 196.09 161.18 164.62 164.62 168.08 175.35 154.27 133.16 115.88 115.88 182.29 189.19 136.61 77.14 108.60 108.60 133.16 147.34 143.89 108.60 126.26 119.33 178.80 164.62 108.60 66.75 105.15 115.88 126.26 140.07 112.05 87.87 98.25 101.70 192.64 192.64 140.07 133.16 154.27 143.89 171.90 206.82 213.75 164.62 150.79 136.61 231.38 238.31 220.65 238.31 234.83 206.82 238.31 273.23 287.40 245.21 217.20 238.31 329.25 357.26 350.36 364.16 360.71 325.80 385.28 399.45 420.19 357.26 332.70 360.71 427.46 486.94 472.76 472.76 479.70 455.47 518.44 518.44 507.71 448.20 458.93 465.86 511.50 570.98 528.79 549.90 532.24 521.88 602.47 584.81 560.25 525.34 560.25 577.91 598.99 627.00 598.99 616.28 595.20 591.75 679.23 686.51 658.50 609.37 651.22 668.85 689.96 721.42 689.96 714.52 703.80 665.40 745.98 745.98
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R Code
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,as.matrix(hd[i])[1,1]) a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1]) 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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