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Data X:
0.78810564 0.78810564 0.67709631 0.17709631 0.27709631 0.71096141 0.81096141 0.71096141 0.24087770 0.14087770 -0.05912230 0.53457538 0.63457538 0.63457538 0.15818935 0.05818935 0.15818935 0.76213817 0.76213817 0.66213817 1.00860791 0.80860791 0.50860791 0.87869162 0.77869162 0.77869162 0.48734744 0.38734744 0.38734744 0.74247301 0.74247301 0.64247301 0.97633811 0.67633811 0.17633811 -0.01265256 -0.21265256 -0.51265256 -0.04492235 -0.04492235 0.15507765 0.14877533 -0.05122467 -0.35122467 -0.32601540 -0.62601540 -0.22601540 -0.42920601 -0.22920601 -0.62920601 -0.10240143 -0.40240143 -0.10240143 -0.04651766 0.25348234 0.25348234 0.10230559 -0.29769441 -0.19769441 0.50230559 0.70230559
Data Y:
0.32855368 0.42855368 0.39703020 0.19703020 0.29703020 0.67325811 0.67325811 0.67325811 0.24509236 0.24509236 -0.15490764 0.16498877 0.16498877 0.26498877 0.15671943 0.15671943 0.35671943 0.86111308 0.96111308 0.96111308 1.29754817 0.99754817 0.39754817 0.12571391 -0.17428609 -0.07428609 -0.01847255 0.08152745 0.18152745 0.47377607 0.37377607 0.17377607 0.45000397 0.25000397 -0.14999603 -0.21847255 -0.31847255 -0.51847255 -0.26601675 -0.36601675 -0.06601675 0.15387966 0.15387966 -0.24612034 -0.22570597 -0.52570597 -0.22570597 -0.18307339 -0.08307339 -0.48307339 -0.43397531 -0.73397531 -0.33397531 0.00529954 0.60529954 0.80529954 0.71744457 0.41744457 0.51744457 1.01744457 1.11744457
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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