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Data X:
0.8261 0.6698 0.5298 -0.3941 -0.8222 -0.3989 0.0482 0.6652 1.1634 0.6756 0.3273 0.3746 0.4142 0.4450 0.6470 0.3020 0.1949 0.1592 -0.2003 0.1388 0.6420 0.5751 0.6404 0.6916 0.8162 0.9539 1.2953 0.9542 0.8657 0.3737 -0.6978 -0.6497 -0.2217 0.0179 0.0356 -0.1155 0.0767 -0.0401 0.0712 -0.1210 -0.2479 -0.4653 -0.7343 -0.5642 -0.5734 -0.4474 -0.7552 -0.7610 -0.2143 -0.1667 -0.6350 -0.7647 -1.2518 -0.7948 -0.1537 0.0351 0.0250 -0.7998 -1.4750 -1.1927
Data Y:
0.6112 0.5840 0.6842 -0.6891 -1.2026 -0.1637 0.8145 1.8764 2.3402 1.2938 0.2466 0.1588 0.1913 0.3426 0.5795 0.1044 -0.2742 0.4333 0.2669 1.0323 1.6045 0.7263 0.4351 0.2871 0.2614 0.3243 0.6935 -0.0753 0.2773 0.4574 0.1379 0.9182 1.2651 0.8310 0.3938 -0.0247 0.2290 0.2010 0.7199 0.3328 0.0547 -0.1410 -0.9896 -0.8393 -0.9211 -0.3444 -0.6909 -1.1006 -0.7894 -1.0100 -1.6239 -1.6399 -2.2518 -1.5901 -1.0551 -0.4071 -0.1571 -0.5985 -1.6240 -1.5202
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
0 seconds
R Server
Big Analytics Cloud Computing Center
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