Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
2527 2194 3200 2716 2726 2352 2695 2649 2065 2639 2537 2292 2710 2312 3090 2675 2811 2666 2937 2615 2229 2479 2419 2406 2558 2098 3313 2799 2401 3022 2505 2978 2209 2469 2592 2450 2230 2371 3125 2800 2639 2785 2617 2804 2191 2321 2527 2410 2260 2152 3228 2293 2713 2731 2315 2728 1911 2388 2482 1958
Sample Range:
(leave blank to include all observations)
From:
To:
Color code
(?)
Number of bins
(?)
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
library(MASS) par1 <- as.numeric(par1) if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2) x <- as.ts(x) #otherwise the fitdistr function does not work properly r <- fitdistr(x,'normal') r bitmap(file='test1.png') myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F) curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Parameter',1,TRUE) a<-table.element(a,'Estimated Value',1,TRUE) a<-table.element(a,'Standard Deviation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,r$estimate[1]) a<-table.element(a,r$sd[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'standard deviation',header=TRUE) a<-table.element(a,r$estimate[2]) a<-table.element(a,r$sd[2]) 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