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Data X:
12071.42 9166.15 15143.76 15225.09 14467.28 13301.01 12188.16 13107.96 17431.92 15168.39 14118.19 16466.02 12597.82 10926.52 17574.80 15011.15 17371.24 15512.70 14631.32 15030.76 21176.07 14058.84 18023.06 18686.89 14730.68 12461.26 18068.74 18947.52 19005.38 14344.85 17079.88 16455.76 21741.50 16491.70 18741.61 20721.60 18398.21 15001.35 18722.45 23421.24 20366.14 15242.37 20842.70 21359.82 21788.71 25125.42 21726.76 27241.50 23913.53 15926.44 24762.17 23762.22 15180.70 12784.82 12199.20 12898.14 14991.55 13208.90 12510.42 15886.08
Data Y:
6368.04 6955.56 12904.96 12746.41 10816.00 12078.01 9801.00 11299.69 16615.21 12343.21 10588.41 16900.00 7569.00 7656.25 13829.76 10691.56 12276.64 12678.76 10506.25 12633.76 18387.36 11046.01 16307.29 18769.00 8281.00 8190.25 14981.76 15202.89 15450.49 14400.00 13947.61 14161.00 20363.29 15276.96 16796.16 22982.56 12188.16 9840.64 17030.25 18550.44 16822.09 16384.00 14786.56 18441.64 20678.44 21756.25 18550.44 24523.56 15202.89 10920.25 19544.04 18632.25 12566.41 14042.25 8911.36 10465.29 12409.96 9840.64 7708.84 13409.64
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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Raw Input
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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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