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Data:
82.75 83.4 84.12 83.88 83.61 83.58 83.58 83.27 83.59 83.64 83.72 83.88 83.61 85.36 87.2 88.28 88.64 88.67 88.34 89.21 89.55 89.65 88.43 91.15 94.11 96.78 97.94 97.57 96.48 96.18 95 93.84 95.54 94.06 93.92 92.55 93.88 92.19 91.42 91.39 89.12 90.27 91.76 95.68 97.54 98.47 100.11 99.9 101.11 98.86 102.71 102.02 100.61 100.62 99.51 98.63 97.44 96.5 94.3 92.92 96.07 95 93.27 91.94 91.62 91.01 90.62 97.72 99.09 99.72 100.22 99.15 101.16 101.8 103.31 101.19 99.09 95.91 94.56 95.76 100.36 102.67 103.58 100.89 103.46 104.86 104.88 104.46 103.83 101 99.36 96.71 95.23 95.62 95.8 94.79 95.39 94.9 94.84 94.68 94.17 94.1 93.84 94.2 97.76 98.26 99.63 98.75
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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