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Data X:
24710.92 23983.59 24434.12 23939.23 24290.02 24117.63 23724.64 22989.44 23716.86 25058.83 25059.00 23579.18 24209.03 24173.67 24706.39 24522.12 24766.15 25940.04 24985.78 24788.00 26544.56 28019.08 27285.71 29161.16 28357.73 27979.91 27543.95 27397.53 27623.59 27736.07 27803.79 27779.55 27524.13 27582.72 28638.95 28825.78 30132.61 29326.85 29075.62 28230.63 28118.36 28173.29 27396.91 24578.55 24504.77 27582.37 26920.31 25426.68 25390.80 25041.16 22769.42 22921.89 26267.63 27364.67 28382.59 29132.81 28214.51 28865.73 24405.35
Data Y:
4.79 5.95 5.46 5.75 5.15 4.96 5.28 5.73 5.75 5.88 6.3 6.74 6.75 7.34 6.64 6.62 6.32 5.32 5.68 6.18 5.02 2.1 4 3 4.73 5.14 5.81 6.24 4.49 4.22 4.88 5.18 5.19 5.06 4.65 4.83 4.6 4.72 4.33 4.97 5.37 4.19 4.54 5.82 5.49 3.28 5.11 6.24 6.41 6.43 8.42 8.23 3.17 2.72 3 3.47 3.88 3.43 4.06
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
0 seconds
R Server
Big Analytics Cloud Computing Center
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