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Data X:
0.111303201 -0.371599129 -0.544498244 -0.672144477 -0.278753982 0.180265125 -0.223157237 -0.647930439 -0.115006714 0.474009056 0.444049469 0.142263723 -0.398007085 -0.306412935 0.14022632 -0.16357871 -0.355567414 -0.766507955 -0.723356535 -0.540373189 -0.442800262 -0.362274443 -0.506612614 -0.470776921 -0.671769894 -0.481586013 -0.435223289 -0.450030542 -0.28629111 -0.209552142 -0.233453609 -0.73921599 -0.789934939 -0.696006808 -0.694917718 -0.26050412 0.7801581 1.288611235 1.378888341 1.548015642 1.701326595 2.464384664 2.03982207 2.429835942 3.002296814 3.843909989 3.166523773 2.881455087 2.132925623 0.469808508 -0.58023403 -0.853988559 -0.448632611 -1.497842086 -1.275860125 -2.067516339 -3.015816436 -3.441007126 -3.601337506
Data Y:
-1.069110747 -0.224600155 -0.519176561 -0.443841916 -0.891681921 -1.156458458 -1.006923284 -0.875826413 -0.540297967 0.171800008 0.591873748 0.389981437 0.673187551 1.247849664 0.778924303 0.678994652 0.484846026 -0.005963015 -0.059886436 0.354323765 -0.043744137 -2.324150774 -0.742260114 -0.928757841 0.452743329 0.698858699 1.179755043 1.546243351 -0.10570001 -0.32691026 0.362464223 0.651949789 0.551157845 0.446572065 0.494726378 0.755766464 1.09262198 0.863112479 0.364138006 0.637611953 0.988913294 -0.167260062 -0.154025582 -0.096528058 -0.45853115 -1.333579753 0.209242602 0.691360013 0.845796569 0.714135402 1.718736881 1.594872844 -2.013866339 -1.988010127 -1.266473304 -0.471055044 -0.459380319 -0.626904673 -1.931655944
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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