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Data:
5.22817665838978e-05 -0.000463820140926281 -4.40505915974873e-05 3.66701376492632e-05 8.27894181489517e-05 0.000120006006809757 0.000171017242898982 -0.000279502333089345 8.75237612852431e-06 -3.91501689793012e-05 -0.000194144893208234 -0.000313101733963577 -5.08960481814131e-05 -0.000233376280487795 -0.000191085353174356 5.24200071684507e-05 -8.82943807301144e-05 3.61935156370373e-05 -8.69486245395421e-07 -0.000275113058485018 -0.000320465698642699 -0.000253480138722013 7.7227498765784e-05 0.000267886776359312 0.000106485389860988 -0.000165627713471103 -7.2254564411878e-05 -0.000135378139756055 -0.000127539859690442 -0.000213768154000569 -0.00018342039892232 -0.000138894755312727 6.85874943347128e-05 -0.000156651547253009 -1.07738256694651e-05 0.000243449321514413 -4.74576674314878e-05 -8.55531074017408e-05 0.000172352041347206 0.000139023530626794 6.7862815596465e-05 0.000195657674159593 -0.000347965684078771 0.000294749351197024 -8.77554455976112e-05 -0.000337265407768624 0.000379267264700164 -0.000141585653849405
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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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