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Data:
66857.20 64722.80 68489.60 71342.90 63542.50 69425.00 58927.90 61009.00 66837.00 66147.60 65982.30 65527.50 65914.60 59189.90 66211.40 66400.80 60167.70 64547.90 57706.20 58642.60 60082.10 63414.80 66044.00 57628.50 62838.80 55758.60 61004.50 66173.40 57489.00 59552.20 57061.80 55895.30 56314.70 61232.80 60014.10 57685.40 60403.10 52349.70 55693.30 65676.10 54898.80 55518.20 53779.10 52340.90 55704.40 60330.30 52837.40 55388.10 60383.40 52070.30 54077.00 62887.80 49212.80 57722.00 53936.80 46991.00 54984.20 56485.10 51277.80 53596.40 54252.50 49413.00 53213.20 58695.30 48723.50 54510.00 49454.10 46136.60 54622.50 50583.00 53224.30 53056.40
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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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Summary of computational transaction
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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