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Data:
14861 14583.3 15305.8 17903.9 16379.4 15420.3 17870.5 15912.8 13866.5 17823.2 17872 17420.4 16704.4 15991.2 16583.6 19123.5 17838.7 17209.4 18586.5 16258.1 15141.6 19202.1 17746.5 19090.1 18040.3 17515.5 17751.8 21072.4 17170 19439.5 19795.4 17574.9 16165.4 19464.6 19932.1 19961.2 17343.4 18924.2 18574.1 21350.6 18594.6 19823.1 20844.4 19640.2 17735.4 19813.6 22160 20664.3 17877.4 20906.5 21164.1 21374.4 22952.3 21343.5 23899.3 22392.9 18274.1 22786.7 22321.5 17842.2 16373.5 16087.1 16555.9 17880.2 16764.5 16049 18288.3 17570.4 15133.4 19334.2 19291.8 20176.7
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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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