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Data:
-23.500 5.90 8.40 7.80 4.80 3.50 8.70 6.80 6.00 3.60 8.70 8.90 8.10 7.00 7.90 8.00 7.50 6.30 7.60 8.40 6.80 8.80 8.70 8.70 7.40 2.80 4.80 -21.10 8.50 9.40 1.80 4.80 5.80 3.30 -9.00 -6.00 -0.90 -17.30 -9.20 -8.10 -20.90 -14.60 -13.90 -20.80 -16.10 -5.00 -7.20 -9.70 -1.40 0.20 2.60 -4.80 -6.20 -2.00 -0.80 -3.10 0.60 0.20 0.30 -0.10 4.30 -3.20 -1.30 1.50 2.50 -2.20 1.70 5.70 2.70 -4.80 -3.10 -0.50 -3.40 -4.70 -5.60 -1.70 -1.80 -5.40 -4.80 -2.80 -4.90 -6.80 -7.60 -6.60 -5.60 -1.40 0.10 -3.70 -5.60 -3.10 -3.80 -5.10 -4.10 -0.30 -0.30 -2.40
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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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Big Analytics Cloud Computing Center
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