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Data X:
14836.78129 4363.00051 -4002.328314 -1812.109098 848.00051 -1406.670666 -4893.45145 -8497.328314 -9477.095569 -4271.766746 24414.12365 33009.34286 33054.56208 37817.57561 26184.90443 25413.23325 21611.23325 20980.90443 19480.35639 12208.68521 8744.014038 13570.57561 43565.35639 47787.35639 46298.24678 32359.01404 22631.90443 24020.57561 21922.90443 17815.12365 9175.890902 6032.562078 6020.342862 8397.671686 35701.00051 41019.00051 32444.43894 13947.43894 1575.110118 -2650.99949 -2245.109098 -8832.218706 -17035.21871 -20944.21871 -29913.67067 -31604.67067 2188.219726 8149.54855 -7346.889882 -15975.65714 -24040.42439 -22757.64361 -20422.08204 -26004.19165 -30769.06851 -33706.8493 -40292.94538 -31693.60302 -1712.712632 1714.835408 -12289.2742 -24404.39734 -34307.64361 -30919.09557 -28222.76675 -28942.32831 -33556.90341 -34260.90341 -43434.80733 -37319.04008 -9341.382428 3.631100644
Data Y:
523.5658454 -3273.146241 -10414.07811 -6902.790198 -2897.146241 -4727.214371 -8504.926458 -9664.078111 -9522.585808 -11281.65394 11711.70211 18606.99002 18669.27793 20458.48232 12320.41419 11765.34606 10978.34606 12736.41419 13642.19441 6972.126279 2179.058149 2409.482322 25864.19441 29791.19441 31499.55045 23225.05815 17110.41419 20072.48232 15823.41419 14852.70211 7120.209802 7283.277932 7607.990019 2783.921889 19491.85376 20415.85376 19612.42959 5818.429585 -1078.502285 -4449.146241 -681.7901979 -4945.434155 -13923.43415 -15768.43415 -26036.21437 -36721.21437 -12942.85833 -12288.92646 -16241.50228 -16101.00998 -19161.51768 -14289.80559 -10476.38142 -13384.02537 -16588.17703 -17771.88911 -23359.32868 -18508.19242 3181.163623 608.3834059 -161.2605507 -6787.108898 -15131.80559 -8601.585808 -1830.653938 -180.0781112 -3207.706675 -2290.706675 -14767.26711 -14364.75941 2786.104328 11306.30872
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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