Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
75.5 83.2 94.5 83.3 92.7 89.8 74.8 81.5 92.8 92.8 91.7 83.5 92.8 91.3 99.5 87.6 95.3 98.5 80.1 84.2 92.4 98.0 92.2 80.0 88.7 87.4 96.1 94.1 91.9 93.6 83.5 80.8 96.3 101.5 91.6 84.0 91.8 90.4 98.0 95.5 90.5 97.1 87.9 79.8 102.0 104.3 92.1 95.9 89.1 92.2 107.5 99.7 92.2 108.9 89.8 89.4 107.6 105.6 100.9 102.9 96.2 94.7 107.3 103.0 96.1 109.8 85.4 89.9 109.3 101.2 104.7 102.4 97.7 98.9 115.0 97.5 107.3 112.3 88.5 92.9 108.8 112.3 107.3 101.8 105.0 103.4 116.7 103.6 108.8 117.0 100.9 100.8 109.7 121.0 114.1 105.5 112.5 113.8 115.3 120.4 111.1 120.1 106.1 95.9 119.4 117.4 98.6 99.7 87.4 90.8 101.3 93.2 95.1 101.9 87.0 86.2 105.0 104.1 99.2 95.2 92.7 99.3 113.5 104.7 100.5 116.2 94.1 94.8 115.1 110.0 108.4 103.9 102.9 107.7 126.7 108.8 117.1 112.2 94.7 102.7 119.1 110.6 109.1 105.3 103.4 103.7 117.0 101.2 105.4 110.3 97.7
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
(?)
# lags (autocorrelation function)
(?)
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Chart options
R Code
par1 <- as.numeric(par1) par2 <- as.numeric(par2) x <- as.ts(x) library(lattice) bitmap(file='pic1.png') plot(x,type='l',main='Run Sequence Plot',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic2.png') hist(x) grid() dev.off() bitmap(file='pic3.png') if (par1 > 0) { densityplot(~x,col='black',main=paste('Density Plot bw = ',par1),bw=par1) } else { densityplot(~x,col='black',main='Density Plot') } dev.off() bitmap(file='pic4.png') qqnorm(x) qqline(x) grid() dev.off() if (par2 > 0) { bitmap(file='lagplot1.png') dum <- cbind(lag(x,k=1),x) dum dum1 <- dum[2:length(x),] dum1 z <- as.data.frame(dum1) z plot(z,main='Lag plot (k=1), lowess, and regression line') lines(lowess(z)) abline(lm(z)) dev.off() if (par2 > 1) { bitmap(file='lagplotpar2.png') dum <- cbind(lag(x,k=par2),x) dum dum1 <- dum[(par2+1):length(x),] dum1 z <- as.data.frame(dum1) z mylagtitle <- 'Lag plot (k=' mylagtitle <- paste(mylagtitle,par2,sep='') mylagtitle <- paste(mylagtitle,'), and lowess',sep='') plot(z,main=mylagtitle) lines(lowess(z)) dev.off() } bitmap(file='pic5.png') acf(x,lag.max=par2,main='Autocorrelation Function') grid() dev.off() } summary(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Descriptive Statistics',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'# observations',header=TRUE) a<-table.element(a,length(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'minimum',header=TRUE) a<-table.element(a,min(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q1',header=TRUE) a<-table.element(a,quantile(x,0.25)) 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.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,'Q3',header=TRUE) a<-table.element(a,quantile(x,0.75)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'maximum',header=TRUE) a<-table.element(a,max(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
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation