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Data X:
26066.71209 27284.35715 23468.63596 17569.48678 18386.10921 299.0147348 1196.834684 831.9365187 -3988.353605 -6242.308346 -9045.288792 12409.07439 16425.02089 16493.8995 12446.60937 6393.58982 7339.105254 5195.536321 6169.581581 2708.764707 1833.691654 2214.942671 -1293.026461 17420.33979 18655.65255 21141.35418 7080.51468 -509.8906811 -5219.817628 -923.8680513 -5615.093362 -14704.27649 -14859.29297 -23144.82279 -33640.81148 -9967.60572 -8086.521352 -13716.06766 -16412.98845 -22166.37118 -17782.91749 -15212.8496 -18459.12841 -25839.97615 -24311.76732 -35008.89387 -34024.08831 -11995.15005 -12507.85168 -13827.37843 -15209.17268 -14177.59243 -4631.119177 5468.32628 9396.261466 13906.25015 15156.79953 8490.379779 12008.25839 32191.57938 34828.90038 32046.77075
Data Y:
52339.13387 52857.89946 54513.76898 44808.30593 43877.74819 -1539.166186 -780.3474886 426.6074601 -5853.923718 -6669.277075 -4528.220486 22960.40885 27396.36728 23116.35574 11275.82457 2849.767977 2846.127101 2354.726405 619.3730493 -5814.178915 -7996.277075 -5566.859073 5517.859176 25186.75525 31253.60975 25979.68364 6840.808357 -3741.200892 -10036.10273 -7205.87757 -13668.70552 -22139.15355 -21982.94341 -31948.23093 -33184.56927 1508.202093 6962.961913 -7956.115461 -15340.48383 -21813.16976 -19399.24713 -15443.27717 -20687.14669 -26276.4169 -24996.37881 -32345.51854 -26129.62824 5820.935265 8439.861371 -5734.159415 -14457.38806 -20251.3257 -15371.34649 -8126.818788 -7979.52202 -9449.183681 -9350.839573 -16076.77722 -10536.78875 17818.46067 23387.7101 9417.303638
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
0 seconds
R Server
Big Analytics Cloud Computing Center
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