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Data:
107.00 116.14 117.18 102.28 109.43 114.28 117.39 116.66 114.29 114.18 114.12 122.62 115.70 127.91 119.55 115.08 116.63 121.38 123.41 120.70 119.40 116.83 116.40 121.67 116.54 129.61 119.93 117.64 121.01 124.20 125.23 123.24 121.58 120.89 117.77 110.91 124.23 127.70 129.45 120.13 122.02 126.59 126.34 125.15 125.02 124.40 127.55 126.63 130.18 136.95 136.81 129.59 133.37 140.02 139.67 139.99 134.57 134.41 134.99 135.70
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R Code
par3 <- '0.01' par2 <- '0.99' par1 <- '0.01' 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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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