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Data X:
20550.02 15876.62 10472.14 5741.66 2632.7 4753.38 42666.74 66105.42 35250.42 38857.54 29869.74 34522.22 33364.22 24973.22 22349.94 18776.5 13502.02 17010.18 53046.74 68228.46 37702.58 30199.38 20879.02 22549.58 9235.5 8149.5 1227.54 6985.74 655.78 4281.02 29801.14 30495.22 17511.14 -1111.86 -7026.3 -9963.34 -9582.58 -17819.34 -25724.38 -28424.86 -33549.98 -34180.74 -3575.82 -4657.42 -25043.5 -33631.98 -39363.82 -34650.9 -35115.38 -37490.06 -39324.22 -41229.1 -47991.86 -41398.38 -15573.18 -15924.98 -28571.5 -35496.54 -37603.14 -27152.02 -20334.22 -18642.22 -17761.78 -22437.02 -22103.94 -15073.86 10675.3 11603.82 -2391.82
Data Y:
9681.09 7146.99 3398.92 -1651.65 -3500.79 -3265.17 9922.07 16760.19 10195.19 12294.52 9496.07 8991.14 7870.14 4861.39 4081.37 1797.66 -662.41 793.28 13753.32 23090.8 15300.13 6707.58 6529.84 4078.38 11434.16 6007.91 2037.02 868.07 -1878.07 4034.59 16446.17 22294.39 21096.42 16379.67 14448.21 10018.35 14059.94 12438.1 2241.99 7107.92 -2135.91 -17792.75 -2007.97 4991.63 988.41 -3731.91 -11543.47 -12240.94 -5909.26 -3994.38 -15871.07 -15220.99 -24112.08 -23953.26 -6313.71 -3272.66 -6009.34 -16395.45 -17384.1 -15708.52 -14853.57 -15305.82 -16625.61 -17450.77 -21566.55 -22416.83 -4813.14 -2620.71 -8157.22
Sample Range:
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bandwidth of density plot
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# lags (autocorrelation function)
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Chart options
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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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Big Analytics Cloud Computing Center
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