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Data X:
-9.122 -0.1328 2.1672 1.6288 4.1716 7.1856 2.0096 -0.7332 0.6508 0.7672 -1.4704 -0.7492 0.2124 2.8372 4.0488 3.2124 4.318 4.0624 5.8284 6.4044 6.6204 4.5496 -0.1492 2.6424 1.5908 2.4748 1.1604 -4.578 2.7388 6.1556 5.5796 6.9016 5.604 6.768 3.314 2.7268 3.5708 3.5372 5.4188 2.344 -0.964 -0.3252 1.6556 0.6368 -6.6752 -8.808 -11.5384 -10.5732 -12.8804 -7.756 -7.2176 -13.2612 -15.1764 -14.1912 -20.34 -20.2924 -17.6652 -15.494 -18.6892 -18.4544 -13.7072
Data Y:
-28.232 -13.6128 -14.4528 -12.7712 -15.2384 -16.7344 -18.3704 -16.0232 -11.6492 -14.7028 -10.8104 -7.5492 -5.5476 -2.2228 -1.4812 -3.5976 -8.312 -7.4576 -2.8216 -2.5256 -2.4896 -6.3904 -12.4092 -5.4076 -6.1492 -7.8852 -11.7896 -18.908 -5.7212 2.8656 1.6096 2.4216 -2.976 -3.442 -4.746 -5.6232 -4.1092 -3.9728 -1.9512 -7.706 -14.754 -21.7552 -18.6744 -21.0932 -31.2252 -33.948 -41.6084 -36.5632 -33.9704 -26.056 -30.1576 -40.3312 -50.2164 -47.2612 -57.94 -65.2624 -64.9752 -68.884 -69.8192 -60.0244 -52.6772
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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