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Data X:
4998.477077 4869.464392 5029.318192 5141.405027 4868.991452 4910.137253 4932.838384 5000.468837 5037.831116 5109.718032 5141.405027 5024.688789 4921.487818 4947.972471 4992.055913 5034.520534 5061.005188 5368.88928 5365.578699 5415.137423 5657.755764 5946.249307 6162.382994 6531.649318 6877.84157 7060.769441 7039.48713 7568.507253 8069.350962 7172.556276 7589.489563 7489.699174 7157.595129 7071.047066 7399.167589 7236.849088 7366.334713 7729.925753 7531.190855 7646.015332 7535.347317 7429.408704 7373.128816 7415.220497 7772.190375 8053.116874 8367.04919 8390.223261 9170.101709 9526.598646 9507.681036 8787.020118 8719.489665 8695.842653 9068.146618 8548.4853 8739.653155 9288.936767 9076.686602 9292.074409
Data Y:
-0.076361633 -0.348454796 -0.283006118 -0.007232932 0.551647427 0.442754039 0.337847343 0.323229476 0.115153871 0.399615998 0.192767068 0.418016111 -0.059699309 0.134576212 0.125069487 0.115869431 0.010144951 0.043597878 0.144313438 0.13358004 0.481139719 0.318783783 0.072067942 -0.107768101 0.017404776 -0.122155466 -0.217555438 -0.031942803 -0.140196797 0.05361772 -0.136542831 -0.21497381 -0.743213372 -0.824506591 -0.595449247 -0.56038681 -0.68839587 -0.767005239 -0.624071644 -0.648911795 -0.624991649 -0.602093732 -0.689929213 -0.799027046 -0.476205295 -0.036925666 0.395198364 0.390189445 0.321623971 0.344547945 0.648636859 0.504424477 0.919042344 1.224153486 1.143704106 1.056047014 0.814748984 0.296068259 -0.758033683 -1.304545078
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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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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