Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
0.5270 0.4720 0.0000 0.0520 0.3130 0.3640 0.3630 -0.1550 0.0520 0.5680 0.6680 1.3780 0.2520 -0.4020 -0.0500 0.5550 0.0500 0.1500 0.4500 0.2990 0.1990 0.4960 0.4440 -0.3930 -0.4440 0.1980 0.4940 0.1330 0.3880 0.4840 0.2780 0.3690 0.1650 0.1550 0.0870 0.4140 0.3600 0.9750 0.2700 0.3590 0.1690 0.3810 0.1540 0.4860 0.9250 0.7280 -0.0140 0.0460 -0.8190 -1.6740 -0.7880 0.2790 0.3960 -0.1410 -0.0190 0.0990 0.7420 0.0050 0.4480
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