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Data:
76.93 79.32 79.35 80.94 80.13 81.38 81.1 81.53 80.46 79.71 78.66 79.96 80.64 81.8 81.06 81.67 79.72 81.28 81.36 85.26 90 93 95.62 102.15 105.73 109.79 113.77 114.3 114.76 113.69 113.88 114.47 112.57 114.43 112.7 113.48 113.05 112.22 111.44 111.67 111.91 111.7 104.26 101.13 98.55 97.06 96.22 95.15 94.54 94.29 93.98 93.76 94.16 93.83 93.97 94.19 94.14 94.24 94.27 94.21 93.45 95.84 98.59 97 96.45 96.48 96.1 95.49 95.85 95.85 98.52 101.77 101.2 102.85 102.98 102.87 100.48 97.59 97.55 99.06 100.43 102.93 104.22 105.26 105.44 106.97 105.82 104.4 102.03 100.17 98.01 96.49 95.63 95.4 94.97 94.68 95.87 94.99 94.65 94.35 94.1 94.21 95.2 95.55 95.68 95.27 95.3 95.93
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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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