Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
100.00 99.76 98.74 99.12 100.22 99.98 100.44 100.19 101.59 102.08 101.43 100.27 101.24 100.92 103.04 102.76 102.36 101.35 101.68 100.29 102.68 102.89 103.30 101.75 103.42 102.92 103.44 103.01 103.45 101.87 100.70 101.24 102.73 102.46 103.90 102.32 102.25 103.21 104.00 103.94 103.08 103.27 103.14 102.63 104.49 104.39 105.49 104.68 103.46 103.38 103.25 104.44 104.47 103.68 104.22 103.18 104.30 105.00 107.23 105.92 106.73 107.72 106.78 107.59 110.69 108.11 109.74 108.76 109.66 110.48 110.25 109.93 110.64 110.44 109.90 110.33 112.38 116.42 117.83 118.28 122.75 124.20 122.34 123.17 121.92 122.68 122.30 123.72 123.78 123.07
Data Y:
100.00 100.22 113.63 115.38 114.95 114.07 111.87 112.53 114.07 113.63 112.09 111.87 110.11 111.43 125.05 127.47 127.03 124.18 120.22 121.98 123.52 123.30 121.98 119.56 118.02 119.34 130.55 134.29 134.73 134.29 130.55 130.77 129.89 129.45 128.35 125.93 124.62 125.05 136.48 138.24 138.02 134.51 130.77 131.21 130.33 129.67 127.47 126.15 125.93 125.93 136.26 137.58 136.26 129.23 124.40 122.42 123.30 120.66 116.92 115.60 112.31 109.67 121.98 124.18 119.12 115.82 112.09 112.97 113.63 111.65 108.35 107.69 103.08 105.05 116.04 117.36 113.85 111.21 110.33 113.41 116.04 117.14 117.80 118.02 115.16 117.80 129.01 131.21 127.69 123.96
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
(?)
# lags (autocorrelation function)
(?)
36
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
Label y-axis:
Label x-axis:
R Code
par1 <- as.numeric(par1) par2 <- as.numeric(par2) x <- as.ts(x) y <- as.ts(y) mylm <- lm(y~x) cbind(mylm$resid) library(lattice) bitmap(file='pic1.png') plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic1a.png') plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic1b.png') plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]') grid() dev.off() bitmap(file='pic1c.png') plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic2.png') hist(mylm$resid,main='Histogram of e[t]') dev.off() bitmap(file='pic3.png') if (par1 > 0) { densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t] bw = ',par1),bw=par1) } else { densityplot(~mylm$resid,col='black',main='Density Plot of e[t]') } dev.off() bitmap(file='pic4.png') qqnorm(mylm$resid,main='QQ plot of e[t]') qqline(mylm$resid) grid() dev.off() if (par2 > 0) { bitmap(file='pic5.png') acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function') grid() dev.off() } summary(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'c',1,TRUE) a<-table.element(a,mylm$coeff[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'b',1,TRUE) a<-table.element(a,mylm$coeff[[2]]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Descriptive Statistics about e[t]',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'# observations',header=TRUE) a<-table.element(a,length(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'minimum',header=TRUE) a<-table.element(a,min(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q1',header=TRUE) a<-table.element(a,quantile(mylm$resid,0.25)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q3',header=TRUE) a<-table.element(a,quantile(mylm$resid,0.75)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'maximum',header=TRUE) a<-table.element(a,max(mylm$resid)) 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