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Data X:
0.918019272 0.523156338 0.318019272 0.418019272 0.602608074 0.597471008 0.612882206 0.343704602 0.343704602 -0.056295398 0.338567536 0.359115801 0.428293404 0.53343047 0.512882206 0.692333942 0.897471008 1.012882206 1.00774514 1.018019272 0.697471008 0.097471008 -0.302528992 -0.602528992 -0.523077256 -0.31794019 -0.171706596 -0.107666058 -0.01794019 -0.107666058 -0.323077256 -0.223077256 -0.41794019 -0.807666058 -0.502528992 -0.602528992 -0.807666058 -0.871706596 -0.99225486 -0.681980728 -0.397391926 -0.397391926 -0.776843662 -1.06656953 -1.356295398 -1.046021265 0.043704602 0.13343047 -0.225473001 -0.999787671 -1.284376473 -0.910061803 0.010486461 0.610486461 0.800212329 0.584801131 0.279664065 0.374526999 0.843704602 0.943704602
Data Y:
2.110170676 1.263534631 0.410170676 0.410170676 0.550078811 0.596714856 0.656806721 0.576990451 0.376990451 0.476990451 1.523626496 1.937082315 1.516898586 0.970262541 0.356806721 0.243350901 0.396714856 0.556806721 0.303442766 0.210170676 -0.003285144 -0.003285144 0.796714856 0.996714856 0.583259036 0.136622991 0.316898586 -0.056649099 -0.063377009 0.043350901 -0.116740964 -0.016740964 -0.363377009 -0.756649099 -0.603285144 -0.903285144 -1.356649099 -0.783101414 -0.996557234 -0.789829324 -1.049921189 -1.349921189 -1.636465369 -1.829737459 -2.023009549 -1.516281639 -0.323009549 0.070262541 0.09717418 -0.036006045 -0.27591418 -0.242733955 0.470721865 0.570721865 0.263993955 -0.39609791 -0.949461865 -0.90282582 -0.423009549 -0.023009549
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
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# lags (autocorrelation function)
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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
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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