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Data:
-0.00027027 -0.007210884 -0.02375 -0.044935065 -0.066666667 -0.063870968 -0.085960265 0.037094017 -0.084294479 -0.045868263 -0.04 0.02 -0.00739726 -0.025751634 -0.019106145 -0.04097561 -0.051428571 -0.002346369 -0.068050314 0.055971223 -0.04741573 -0.047039106 -0.025977011 0.031976048 0.00125 0.007951807 -0.016649215 -0.030561798 -0.020697674 0.003870968 -0.053619632 0.059735099 -0.037291667 -0.030847458 0.009528796 0.075555556 0.054285714 0.02 0.038957346 0.014186047 -0.016082474 -0.02040404 -0.048181818 0.063209877 -0.026153846 -0.010150754 -0.01 0.03734104 0.004126984 -0.00688172 -0.026728972 -0.00688172 0.00989899 -0.023269231 -0.000408163 0.025649718 -0.01030303 0.010990991 0.039323671 0.109385475 0.082200957 0.005849057 0.057383178 0.04173913 0.029389671 0.036736402 0.037857143 0.129289617 0.059473684 0.064843049 0.121123596 0.117560976 0.10125 0.044390244 0.048248588 0.013975904 0.007654321 0.025464481
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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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