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Data X:
2.756.76 2.849.27 2.921.44 2.981.85 3.080.58 3.106.22 3.119.31 3.061.26 3.097.31 3.161.69 3.257.16 3.277.01 3.295.32 3.363.99 3.494.17 3.667.03 3.813.06 3.917.96 3.895.51 3.801.06 3.570.12 3.701.61 3.862.27 3.970.10 4.138.52 4.199.75 4.290.89 4.443.91 4.502.64 4.356.98 4.591.27 4.696.96 4.621.40 4.562.84 4.202.52 4.296.49 4.435.23 4.105.18 4.116.68 3.844.49 3.720.98 3.674.40 3.857.62 3.801.06 3.504.37 3.032.60 3.047.03 2.962.34 2.197.82 2.014.45 1.862.83 1.905.41 1.810.99 1.670.07 1.864.44 2.052.02 2.029.60 2.070.83 2.293.41 2.443.27
Data Y:
10.001.60 10.411.75 10.673.38 10.539.51 10.723.78 10.682.06 10.283.19 10.377.18 10.486.64 10.545.38 10.554.27 10.532.54 10.324.31 10.695.25 10.827.81 10.872.48 10.971.19 11.145.65 11.234.68 11.333.88 10.997.97 11.036.89 11.257.35 11.533.59 11.963.12 12.185.15 12.377.62 12.512.89 12.631.48 12.268.53 12.754.80 13.407.75 13.480.21 13.673.28 13.239.71 13.557.69 13.901.28 13.200.58 13.406.97 12.538.12 12.419.57 12.193.88 12.656.63 12.812.48 12.056.67 11.322.38 11.530.75 11.114.08 9.181.73 8.614.55 8.595.56 8.396.20 7.690.50 7.235.47 7.992.12 8.398.37 8.593.01 8.679.75 9.374.63 9.634.97
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')
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Computing time
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R Server
Big Analytics Cloud Computing Center
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