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Data X:
-203.7281445 -196.9726865 -200.1506505 -210.2286145 -227.7644485 -237.2983405 -253.9913085 -241.3963985 -228.0971345 -237.3109325 -224.9140805 -268.2554745 -261.5617705 -255.7862185 -275.3728905 -311.2430865 -341.7372605 -359.0081925 -367.5345825 -435.1730325 -538.9686165 -461.3408165 -496.8153665 -527.5102765 -521.4649985 -531.7308405 -522.8233385 -535.0308405 -504.9279585 -506.8039805 -548.4584365 -603.5787345 -621.9315145 -574.0368705 -575.6959465 -540.1453745 -530.8674105 -544.6785305 -490.7492585 -456.9609105 -496.5877705 -545.7175125 -595.7901205 -583.8247485 -549.3199245 -535.2332525 -538.5218665 -493.5669405 -447.9817405 -290.5399385 -222.1932505 -176.5930465 -193.1584185 -186.7603605 -201.9533285 -243.8499145 -265.3850125 -299.7941905 -315.8387325 -391.1181065 -392.8294925
Data Y:
-168.2281445 -192.0726865 -201.9506505 -185.3286145 -213.8644485 -230.8983405 -216.2913085 -206.3963985 -192.8971345 -205.3109325 -211.4140805 -227.6554745 -206.6617705 -222.6862185 -248.7728905 -274.7430865 -326.1372605 -348.8081925 -338.4345825 -409.9730325 -493.5686165 -437.6408165 -462.6153665 -473.8102765 -429.9649985 -475.4308405 -454.0233385 -432.7308405 -466.4279585 -467.8039805 -484.7584365 -541.9787345 -548.9315145 -533.1368705 -523.8959465 -472.0453745 -447.3674105 -490.4785305 -432.1492585 -379.1609105 -430.2877705 -540.0175125 -537.7901205 -533.7247485 -511.1199245 -524.0332525 -504.8218665 -430.8669405 -381.5817405 -223.7399385 -166.8932505 -86.49304654 -51.05841854 -143.5603605 -117.5533285 -151.8499145 -211.0850125 -272.8941905 -295.3387325 -365.2181065 -351.6294925
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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