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Data X:
2.97 3.04 3.12 3.21 3.34 3.45 3.74 4.02 4.24 4.87 5.62 6.02 5.98 5.89 5.76 5.58 5.39 5.19 5.16 5.2 5.25 5.26 5.21 5.18 5.13 5.03 5.01 4.87 4.86 4.82 4.69 4.65 4.61 4.47 4.37 4.29 4.2 4.19 4.09 3.88 3.87 3.74 3.61 3.43 3.29 3.18 3.07 3.02 2.97 2.98 3.01 3.06 3.12 3.16 3.19 3.21 3.27 3.36 3.45 3.52 3.58 3.62 3.5 3.43 3.41 3.48 3.63 3.76 3.8 3.72 3.67 3.58 3.47 3.43 3.55 3.65 3.7 3.7 3.93 4.15 4.24
Data Y:
4.62 4.64 4.57 4.49 4.48 4.5 4.52 4.63 4.75 4.99 5.28 5.33 5.26 5.14 4.99 4.85 4.83 4.83 4.88 4.91 4.93 4.93 4.95 4.95 4.88 4.78 4.61 4.46 4.42 4.43 4.41 4.4 4.36 4.36 4.38 4.4 4.37 4.32 4.18 4.04 4 3.97 3.94 3.93 3.89 3.89 3.88 3.9 3.9 3.95 4.02 4.07 4.17 4.27 4.32 4.38 4.45 4.71 4.96 4.95 4.78 4.78 4.68 4.65 4.64 4.74 4.76 4.61 4.75 4.73 4.68 4.68 4.75 4.79 4.81 4.92 4.99 5.18 5.29 5.48 5.66
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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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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