Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
26 20 27 25 17 16 20 18 19 22 30 40 26 36 31 41 24 27 19 30 31 26 15 33 28 27 21 27 21 30 30 33 35 26 27 25 30 20 8 24 25 28 23 21 21 26 26 30 34 30 18 4 31 18 14 21 37 24 29 24 31 21 31 26 24 18 21 29 24 21 30 20 30 24 26 27 24 23 26 25 18 30 25 27 8 21 26 24 30 27 24 25 21 24 24 24 24 24 40 22 31 26 20 19 15 22 25 28 23 25 26 32 1 24 11 31 26 0 19 8 27 31 24 20 8 22 33 33 31 33 35 21 24 25 31 22 27 24 27 26 16 23 24 21 30 37 24 29 0 0 0 0 0 0 20 31 0 0 0 5 1 23 0 16
Data Y:
170650 86621 127843 152526 92389 38778 316392 32750 123444 137034 176816 143205 113286 195452 144513 263581 183271 210763 113853 159968 174585 294675 96213 116390 146342 152647 166661 175505 112485 198790 191822 140267 221991 75339 247985 167351 266609 122024 80964 215183 225469 125382 141437 81106 93125 318668 78800 161048 236367 131108 131096 24188 267003 65029 100147 178549 186965 197266 217300 149594 263413 209228 145699 187197 150752 131218 118697 147913 155015 96487 128780 71972 140266 152455 110655 204822 216052 113421 103660 128390 105502 299359 141493 148356 80953 109237 102104 233139 176507 118217 142694 152193 126500 174710 187772 140903 155350 202077 213875 252952 166981 190790 106351 43287 127493 132143 157469 197727 88077 94968 191753 153332 22938 125927 61857 103749 269909 21054 174409 31414 200405 139456 78001 82724 38214 91390 197612 137161 251103 209835 269470 139215 77796 197114 291962 56727 254843 105908 170155 136745 86706 251448 152366 173260 212582 87850 148636 185455 0 14688 98 455 0 0 137891 201052 0 203 7199 46660 17547 73567 969 106662
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
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation