Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
260288 261544 259886 257006 259670 258873 264416 263596 262586 260237 261690 259295 264170 264451 265538 261723 266189 265073 267007 266376 267406 262742 260300 263074 265940 264771 268403 264264 264118 266817 269296 269001 266707 267507 267510 267420 270845 270671 273653 271567 268372 268160 267879 271142 271323 269478 271008 269145 271684 273582 279475 276188 278422 281084 278618 280738 288897 282129 286406 284288 286139 288275 287670 286864 288798 288316 286915 288006 293338 303730 306248 305700 314849
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
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation