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Data:
-0.0361910293346112 -0.130573884966384 0.0508918469276857 0.285401362098854 -0.144383808058777 -0.476406414178597 0.278108962203585 -0.0138995480760208 -0.222087591687949 0.209175033072651 0.0192739441821673 0.125857350082273 0.168126817416534 0.274716043721393 -0.115012818239837 -0.0528152166781983 0.0480099460498225 -0.271042927666295 -0.0342951777172496 0.0627605675580158 0.307448877628319 -0.0499740104559924 0.217631447221166 0.588245078469366 -0.104976668923445 0.0161271326299674 0.360593922797499 0.34885308223225 0.549125366865315 -0.149732507116426 -9.69800498562644e-05 -0.110243693744648 0.519793940008804 -0.222103155113966 -0.532213370012485 -0.373612664474175 -1.5811601864973 -0.226230409909392 -0.351379591715873 0.415088956092972 -0.551569595958837 0.00975519186112273 0.440089664424697 0.484637284027762 -0.101777761975125 -0.635031201521745 0.562248596196737 -0.52856053825146 0.56712813530769
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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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