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Data X:
1089 1521 2025 2116 2025 2025 2401 2500 2916 3481 3364 3136 2304 2500 2704 2809 3025 1849 1764 1444 1681 1681 1521 1156 729 225 196 961 1681 1849 2116 1764 2025 2025 1600 1225 1296 1444 1521 1024 576 441 144 841 1296 961 784 900 1444 729 1600 1600 1936 2209 2025 1764 1444 2116 1369 1681 1600 1089 1156 1296 1296 1444 1764 1225 625 576 484 729 289 900 900 1156 1369 1296 1089 1089 1089 1369 1600 1225 1369 1849 1764 1089 1521 1600 1369 1936 1764 1849 1600 900 900 961 324 576 484 676 784 529 289 144 81 361 441 324 324 225 576 324 361 900 1089 1225 1296 2209 2116
Data Y:
3844 4096 3844 4096 4096 4761 4761 4225 3136 3364 2809 3844 3025 3600 3481 3364 2809 3249 3249 2809 2916 2809 3249 3249 3025 2401 2500 2401 2916 3364 3364 2704 3136 2704 3481 2809 2704 2809 2601 2500 3136 2704 2116 2304 2116 2304 2304 2401 2809 2304 2601 2304 2500 3025 2704 2809 2704 3025 2809 2809 3136 2916 2704 3025 2916 3481 3136 3136 2601 2809 2704 2601 2116 2401 2116 3025 3249 2809 2704 2809 2500 2916 2809 2500 2601 2704 2209 2601 2401 2809 2704 2025 2809 2601 2304 2304 2304 2304 1600 1849 1600 1521 1521 1296 1681 1521 1600 1521 2116 1600 1369 1369 1936 1681 1600 1296 1444 1849 1764 2025 2116
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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Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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