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Data X:
94.3 99.4 115.7 116.8 99.8 96.0 115.9 109.1 117.3 109.8 112.8 110.7 100.0 113.3 122.4 112.5 104.2 92.5 117.2 109.3 106.1 118.8 105.3 106.0 102.0 112.9 116.5 114.8 100.5 85.4 86.6 109.9 100.7 115.5 100.7 99.0 102.3 108.8 105.9 113.2 95.7 80.9 113.9 98.1 102.8 104.7 95.9 94.6 101.6 103.9 110.3 114.1 96.8 87.4 111.4 97.4 102.9 112.7 97.0 95.1 96.9 98.6 111.7 109.8 89.9 87.4 104.5 98.1 102.7 105.4 97.0 97.4
Data Y:
16.4 17.8 22.3 22.8 18.3 22.4 23.9 21.3 23.0 21.4 21.2 20.9 17.9 20.7 22.2 19.8 17.7 19.6 20.8 19.8 18.6 21. 18.6 18.9 17.3 20.0 19.9 19.5 16.2 17.6 19.8 19.4 17.2 21.1 17.8 17.5 18.0 19.1 17.7 19.2 15.1 16.3 18.6 17.2 17.8 19.1 16.6 16.0 16.7 17.4 17.9 17.8 13.9 15.9 17.9 15.4 16.4 17.9 15.3 14.6 14.9 15.0 16.7 16.3 11.7 15.1 15.5 15.0 15.4 16.0 14.7 14.8
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
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# lags (autocorrelation function)
(?)
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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Computing time
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R Server
Big Analytics Cloud Computing Center
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