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Data X:
-0.115348744 -0.007430684 0.133083506 0.10990307 -0.044227883 -0.027962073 0.124923169 0.069938271 0.10207697 0.074946808 0.033187327 0.032240529 -0.099390858 0.015707515 0.144498623 0.054184893 -0.105055816 -0.182509537 0.023413818 -0.034617275 -0.030773287 0.088969168 -0.018347742 0.015141613 -0.083681811 0.012257933 0.063956725 0.050285253 -0.148793116 -0.211572756 0.038835971 -0.054887315 -0.064381527 0.040560126 -0.096653186 -0.03730336 -0.058279231 0.01374282 0.012929942 0.031409519 -0.167303701 -0.234454594 0.071595677 -0.058758499 -0.029159212 -0.003939614 -0.04168033 -0.040265025 -0.036687857 0.120682129 0.186906774 0.188095521 -0.048823116 -0.02473896 0.058343008 0.047528578 0.098720517 0.159550648 0.025284856 0.032824856
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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36
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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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0 seconds
R Server
Big Analytics Cloud Computing Center
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