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Data X:
-4305.27 -644.87 -2540.32 -1512.92 -1307.62 -2973.97 -1802.42 340.42 -1597.07 -1779.22 -850.42 -3760.12 -3088.73 -316.68 -1314.97 990.38 123.02 -844.38 -609.18 2823.23 -1186.57 -53.58 745.18 -1426.87 -821.22 1824.68 1466.89 1846.63 -908.92 854.39 683.63 3226.03 287.23 1457.39 2568.19 1111.59 655.84 2277.64 3474.73 2698.27 165.27 1392.87 1633.02 1458.01 2264.26 -518.65 2353.89 -218.96 -1851.00 1250.15 1356.80 47.52 -1823.32 -2457.82 -1837.72 648.05 -894.10 -1050.84 1707.86 564.62
Data Y:
-5170.50 -497.52 -1876.75 -1192.58 -2008.81 -2833.00 -1953.88 555.46 -1245.97 -1986.18 -629.35 -3235.95 -3666.73 -417.52 -877.69 437.22 -1671.54 -1294.54 -1190.94 2369.91 -1462.35 124.86 1882.04 -1498.67 -1616.48 2041.89 1984.77 1598.30 -1359.99 1549.07 860.58 3527.58 672.48 2057.94 3652.74 1591.34 639.43 2854.25 3826.51 2640.07 -1553.31 1778.22 1834.93 1420.19 2381.17 -149.45 2519.81 247.92 -2280.63 1897.08 1763.13 -715.00 -2669.55 -2334.49 -1822.31 421.48 -1048.11 -1109.28 1567.45 671.20
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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