Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
100.00 106.54 127.63 141.72 147.95 142.16 147.95 155.82 164.13 159.16 147.14 159.16 178.85 200.44 189.43 160.16 157.02 168.91 173.19 175.83 158.78 166.96 171.24 179.55 191.00 196.41 206.80 208.94 224.86 217.31 229.96 252.36 255.25 290.37 269.67 240.53 252.86 265.51 299.31 297.42 277.09 313.59 335.75 370.67 375.33 358.65 334.80 335.05 364.07 350.47 350.16 393.46 405.29 406.86 426.12 422.97 373.63 335.18 329.89 346.32 100.00 106.54 127.63 141.72 147.95 142.16 147.95 155.82 164.13 159.16 147.14 159.16 178.85 200.44 189.43 160.16 157.02 168.91 173.19 175.83 158.78 166.96 171.24 179.55 191.00 196.41 206.80 208.94 224.86 217.31 229.96 252.36 255.25 290.37 269.67 240.53 252.86 265.51 299.31 297.42 277.09 313.59 335.75 370.67 375.33 358.65 334.80 335.05 364.07 350.47 350.16 393.46 405.29 406.86 426.12 422.97 373.63 335.18 329.89 346.32
Data Y:
100.00 100.28 100.00 98.62 98.35 98.35 104.68 104.13 103.58 104.68 104.41 105.79 107.99 108.54 107.99 109.09 107.99 109.09 115.43 115.98 115.70 115.15 112.95 115.15 117.36 117.91 118.46 116.80 116.53 117.63 121.49 123.69 124.52 127.27 125.34 127.00 127.00 127.55 127.27 125.62 125.34 125.62 130.03 130.03 129.75 128.10 126.45 128.10 128.93 128.65 127.55 126.72 127.27 127.00 131.13 131.13 129.75 124.79 122.04 121.76 100.00 100.28 100.00 98.62 98.35 98.35 104.68 104.13 103.58 104.68 104.41 105.79 107.99 108.54 107.99 109.09 107.99 109.09 115.43 115.98 115.70 115.15 112.95 115.15 117.36 117.91 118.46 116.80 116.53 117.63 121.49 123.69 124.52 127.27 125.34 127.00 127.00 127.55 127.27 125.62 125.34 125.62 130.03 130.03 129.75 128.10 126.45 128.10 128.93 128.65 127.55 126.72 127.27 127.00 131.13 131.13 129.75 124.79 122.04 121.76
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