Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
-8.420276058 5.603810549 7.227897157 -0.439987367 -8.023929628 -10.08378528 -10.65969868 -2.827583199 -3.339265638 -2.699121292 5.708907577 -19.42686147 -11.31080373 5.505254006 2.529340614 3.06145609 -4.822486171 -5.698399564 -5.450226349 7.438091212 0.070206688 5.602322165 8.934437641 -17.34950462 -6.409360275 9.214726333 12.15487068 5.578957286 1.503043893 -0.488927238 -0.46484063 12.15121711 4.459245977 6.675303715 11.79939032 -12.67652307 -2.168494201 10.64756354 14.39573675 8.711794491 -0.832003425 4.284054313 7.172371874 9.140978126 10.51323795 9.58549777 13.30155551 -10.16632902 -1.210126931 10.14607515 8.762132891 -0.865607287 -10.54954955 -12.32546294 -11.6094052 -0.077289726 -10.75320312 -6.588972166 -1.932770082 -22.20868347
Data Y:
0.650033625 0.669304839 0.088576053 -0.385728995 -0.272881519 -0.04076283 0.078508384 0.004203336 -0.225135547 -0.293016857 -0.486593119 0.264796785 0.37764426 0.390491736 0.20976295 0.135457902 0.248305378 0.467576592 0.506119019 0.476780137 0.402475088 0.22817004 -0.046135008 0.166712468 0.098831158 0.118102371 0.050221061 -0.030507725 -0.011236511 0.095187227 0.114458441 0.027305917 0.133729654 -0.15342287 -0.634151656 -0.314880442 -0.508456704 -0.795609228 -0.7570668 -0.744219325 -0.499253159 -0.386405683 -0.515744566 -0.680846069 -1.023032427 -1.265218786 -0.85237131 0.373323642 0.618289807 0.263255973 -0.323896551 -0.56608291 -0.253235434 0.56603578 0.878883256 0.904578208 0.623849422 0.275239325 0.420205491 1.139476705
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
(?)
# lags (autocorrelation function)
(?)
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