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Data X:
-1.35014 -1.75014 -4.74826 -5.39779 -6.54638 -4.39779 -5.29685 -3.74826 -6.99591 -8.39497 -9.09403 -8.1445 -7.19497 -7.14544 -8.44544 -7.19685 -5.24826 -7.14638 -6.09685 -5.79685 -5.14732 -3.59873 -3.0492 -1.60061 -2.29967 -1.45014 -1.00061 -1.59967 -1.7492 -1.8492 -0.20061 0.34892 0.24892 0.79845 0.54892 -0.59967 0.14986 -0.59967 -0.30061 0.24892 -0.30061 2.09751 0.64892 3.39657 -0.00061 0.44892 1.39845 3.09751 2.64798 4.09657 0.79845 1.79751 3.09657 1.29845 3.04704 1.84798 3.19657 2.64704 2.89751 3.79751
Data Y:
-0.8651 -0.9651 -3.5609 -4.18485 -5.4567 -3.68485 -4.93275 -3.9609 -7.48065 -8.92855 -9.67645 -8.3525 -7.42855 -7.0046 -8.1046 -6.83275 -4.9609 -6.7567 -5.83275 -5.83275 -5.6088 -4.33695 -3.713 -2.04115 -2.88905 -2.2651 -2.04115 -2.68905 -3.013 -3.113 -1.34115 -0.7172 -0.8172 -0.39325 -1.0172 -2.78905 -2.3651 -2.58905 -1.14115 -0.0172 -0.24115 1.85465 0.2828 2.80255 -0.54115 -0.2172 0.30675 1.25465 0.6307 2.20255 -0.29325 1.15465 2.20255 0.40675 1.9786 0.9307 2.30255 1.6786 1.35465 1.75465
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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36
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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')
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Raw Input
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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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