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Data X:
-11.152 -1.5796 13.16 11.1072 -5.6192 -3.8776 13.7234 7.109 10.9492 7.6378 2.6788 2.4724 -10.7344 0.574 15.1298 4.6936 -11.3734 -18.5268 1.4216 -4.6246 -4.2308 8.5854 -2.922 0.5006 -9.2324 0.2036 5.65 4.1602 -15.015 -20.315 2.9446 -6.449 -7.137 3.139 -9.8002 -4.357 -6.117 0.6406 0.589 2.3694 -15.0224 -19.9452 6.3754 -5.8596 -3.3378 -1.0326 -4.4502 -4.275 -3.768 11.3846 18.4804 18.5824 -4.7104 -2.5836 5.172 4.139 9.136 15.4814 1.9896 2.7668
Data Y:
-9.314 -5.0234 9.814 8.1308 -10.2608 -15.3104 4.6961 -2.2175 6.0038 -1.2903 2.5262 1.1646 -7.4196 5.355 14.0077 4.5124 -3.8231 -16.2402 8.6444 0.0841 -3.0662 10.6491 -2.219 -1.2421 -5.2066 5.9774 9.549 8.2253 -6.2735 -21.3735 8.4939 3.0555 -4.8665 10.9275 -3.7873 -5.1465 -1.1365 5.8179 3.1025 10.4451 -6.8916 -21.2798 11.7841 -4.1934 -0.0117 1.7321 -6.8123 -7.9135 -0.168 2.0539 8.7166 12.7296 -4.5136 -13.8994 10.342 -3.6225 1.558 11.2231 -4.3136 -5.8018
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 Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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