Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
180.818 183.186 183.613 184.641 187.881 190.157 190.379 191.835 192.797 193.299 197.549 198.296 199.297 199.746 200.156 203.077 204.386 206.771 206.893 207.533 208.108 211.655 213.361 213.511 213.923 216.046 216.548 216.886 217.465 218.761 220.553 221.588 223.166 226.731 229.641 232.444 232.669 235.577 236.302 238.502 240.755 241.171 242.205 242.344 246.542 249.148 250.407 251.422 257.102 257.567 260.642 261.596 262.517 262.875 263.906 265.777 266.793 274.482 275.562 278.741
Chart options
R Code
library(Hmisc) m <- mean(x) e <- median(x) bitmap(file='test1.png') op <- par(mfrow=c(2,1)) mydensity1 <- density(x,kernel='gaussian',na.rm=TRUE) plot(mydensity1,main='Density Plot - Gaussian Kernel',xlab='Median (0 -> full line) | Mean (0 -> dashed line)',ylab='density') abline(v=e,lty=1) abline(v=m,lty=5) grid() myseq <- seq(0.01, 0.99, 0.01) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) plot(myseq,hd,col=2,main='Harrell-Davis Quantiles',xlab='quantiles',ylab='Median (0 -> full) | Mean (0 -> dashed)') abline(h=m,lty=5) abline(h=e,lty=1) grid() par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Median versus Mean',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(x)) 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
2 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation