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Data:
5221.3 5115.9 5107.4 5202.1 5307.5 5266.1 5329.8 5263.4 5177.1 5204.9 5185.2 5189.8 5253.8 5372.3 5478.4 5590.5 5699.8 5797.9 5854.3 5902.4 5956.9 6007.8 6101.7 6148.6 6207.4 6232 6291.7 6323.4 6365 6435 6493.4 6606.8 6639.1 6723.5 6759.4 6848.6 6918.1 6963.5 7013.1 7030.9 7112.1 7130.3 7130.8 7076.9 7040.8 7086.5 7120.7 7154.1 7228.2 7297.9 7369.5 7450.7 7459.7 7497.5 7536 7637.4 7715.1 7815.7 7859.5 7951.6 7973.7 7988 8053.1 8112 8169.2 8303.1 8372.7 8470.6 8536.1 8665.8 8773.7 8838.4 8936.2 8995.3 9098.9 9237.1 9315.5 9392.6 9502.2 9671.1 9695.6 9847.9 9836.6 9887.7 9875.6 9905.9 9871.1 9910 9977.3 10031.6 10090.7 10095.8 10126 10212.7 10398.7 10467 10543.6 10634.2 10728.7 10796.4 10875.8 10946.1 11050 11086.1 11217.3 11291.7 11314.1 11356.4 11357.8 11491.4 11625.7 11620.7 11646 11700.6
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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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