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Data X:
286.1 307 358.1 341.8 378.8 375.2 295.6 362.7 409.6 336.8 389.1 389.3 355.9 542 648.4 452 582.4 506.5 555.5 530.4 609.4 543.9 616.2 634.6 541.7 549.8 627.6 797.4 689.8 1576.6 1572.1 1626.4 1972.4 1509.6 1584.9 1880 1324 1777.7 2172.4 1780.3 2134.9 1838.4 1557 1755.2 1702 1577.5 1485.9 2179.1 1740.9 1724.5 2328.1 1774.1 2224.2 1536.3 1521.2 2051.8 2483.1 1929.8 1808.6 2584.9 1997.9 1639.9 2379.1 1715 2750.9 1865.4 1647.4 2180.4 2593 2057.2 2635.8 2315.4 1863.6 2038 2235.8 2222.1 2636.9 2076.8 1935.5 2086.3 2470.9 1854.6 2041.3 2170.8 1905.5 2130.2 2791.2 2539.7 2661.3 1764.9 2176.9 2458.5 2179 2242.5 2089.6 2661.6 2112 2367.3 2543 2603.9 3146.7 1789.2 2114.8 2236.3 2288.1 2173.2 1877.7 2807.4 2357.4 2107.7 2856.8 2510.8 2875 2229.7 2055.1 2545.4 2775.1 2252.2 2091.7 2433
Data Y:
11881.4 10374.2 13828 13490.5 13092.2 13184.4 12398.4 13882.3 15861.5 13286.1 15634.9 14211 13646.8 12224.6 15916.4 16535.9 15796 14418.6 15044.5 14944.2 16754.8 14254 15454.9 15644.8 14568.3 12520.2 14803 15873.2 14755.3 12875.1 14291.1 14205.3 15859.4 15258.9 15498.6 15106.5 15023.6 12083 15761.3 16943 15070.3 13659.6 14768.9 14725.1 15998.1 15370.6 14956.9 15469.7 15101.8 11703.7 16283.6 16726.5 14968.9 14861 14583.3 15305.8 17903.9 16379.4 15420.3 17870.5 15912.8 13866.5 17823.2 17872 17420.4 16704.4 15991.2 16583.6 19123.5 17838.7 17209.4 18586.5 16258.1 15141.6 19202.1 17746.5 19090.1 18040.3 17515.5 17751.8 21072.4 17170 19439.5 19795.4 17574.9 16165.4 19464.6 19932.1 19961.2 17343.4 18924.2 18574.1 21350.6 18594.6 19823.1 20844.4 19640.2 17735.4 19813.6 22160 20664.3 17877.4 20906.5 21164.1 21374.4 22952.3 21343.5 23899.3 22392.9 18274.1 22786.7 22321.5 17842.2 16373.5 15993.8 16446.1 17729 16643 16196.7 18252.1
Sample Range:
(leave blank to include all observations)
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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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Summary of computational transaction
Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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