Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
1.6 2 2.6 3 2.6 2.9 2.5 2.4 1.5 1.1 0.6 0.9 1.1 1.5 1.7 1.2 0.4 -0.7 -1.4 -1.6 -1.2 -0.4 -0.2 -0.3 -0.5 0 -0.5 0.2 0.7 1.6 2.6 3.3 3.3 3.2 3.5 3.9 4.5 4.6 6.6 7.1 8.9 8.8 8.5 7.6 7.5 7.5 6.1 6.3 8.4 7.1 5.6 4.2 2.1 1.2 0.9 1.4 1.7 1.7 1.9 1.3 -0.7 0.3 0.8 0.9 1.1 2.5 2.7 3.3 4.2 3.8 3.8 3.2 2.9 1.9 1.7 1.6 1.7 1.2 0.7 -0.2 -1.5 -1.2 -1 0 -0.6 0.7 1.3 0.8 1 0.5 0.3 1 1 1.1 1.5 1.5 2 1.7 0.6 1.2 1.5 2.1 3.2 3.9 4.6 4.2 4.4 3.7 3.7 2.8 2.9 3.9 3.1 3 2.8 2.4 2.1 3.1 3 3.1 3.3 3.3 3.8 3.1 3.9 4 4.4 3.7 3.6 3.4 2.8 2.8 2.6 3.3 2.4 1.6 0.7 0 -1.1 -1.2 -1.3 -1.6 -1.3 -1.6 -1.1 -1 0.3 1.2 0.7 1.1 2.1 2.5 2.3 2.3 2.6 3.2 2.2 2.7 2.2 1.4 2.4 2 1.3 1.1 1.4 1.8 1.9 1.6
Sample Range:
(leave blank to include all observations)
From:
To:
lowest quantile
highest quantile
step size
Chart options
Title:
Label y-axis:
Label x-axis:
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')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation