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Data:
-0.0458219311540836 -3.61034238186063 -0.853814452828177 2.53527041373087 8.39325314204064 6.2575898456346 -0.377995826634012 1.08010829631239 -11.1573310467422 0.970799934298258 -3.35754339337974 0.58797105881135 2.23897146436900 -6.53401224240524 4.95107302609029 -8.69198650507936 1.53082486114423 4.06552732307529 -2.16858484681198 -1.14101331906545 2.12572360236892 2.31902426177582 5.16416545706942 4.70580776574552 1.83243115177358 5.48921744319778 8.7493611715722 -14.7109505532558 -1.00713750604001 -2.51112374371448 3.49151269150035 -4.2313335253486 -1.80963719528798 -4.89179463898519 -1.43701193391923 3.42035661578196 -10.3566454703673 -3.08502514062412 -4.66281833041767 0.584634380621076 -0.869863134006014 1.84999028273394 -2.65763276997209 -0.203499395537907 -4.38510067862018 3.71207135321748 4.44871977825867 -1.19818348727787
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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
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Big Analytics Cloud Computing Center
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