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Data:
98.01 99.2 100.7 106.41 107.51 107.1 99.75 98.96 107.26 107.11 107.2 107.65 104.78 105.56 107.95 107.11 107.47 107.06 99.71 99.6 107.19 107.26 113.24 113.52 110.48 111.41 115.5 118.32 118.42 117.5 110.23 109.19 118.41 118.3 116.1 114.11 113.41 114.33 116.61 123.64 123.77 123.39 116.03 114.95 123.4 123.53 114.45 114.26 114.35 112.77 115.31 114.93 116.38 115.07 105 103.43 114.52 115.04 117.16 115 116.22 112.92 116.56 114.32 113.22 111.56 103.87 102.85 112.27 112.76 118.55 122.73
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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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