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Data X:
-0.533226576 -0.515978057 -0.477093095 -0.496333869 -0.558827111 -0.581203315 -0.559508891 -0.526763132 -0.485216419 -0.488433897 -0.534946188 -0.523998828 -0.540816723 -0.552659929 -0.562550228 -0.572475926 -0.551776608 -0.529103402 -0.475390277 -0.471325588 -0.483238705 -0.488910901 -0.480923869 -0.463863837 -0.441495171 -0.434380513 -0.43007547 -0.430772563 -0.403799892 -0.43120666 -0.452248414 -0.457170432 -0.467120671 -0.471652125 -0.504228836 -0.479929931 -0.502923197 -0.524137056 -0.524042456 -0.541890172 -0.48902791 -0.472776364 -0.489501826 -0.485214052 -0.46030773 -0.468320878 -0.470662125 -0.443154969 -0.455964052 -0.489908091 -0.480143313 -0.493100702 -0.500777231 -0.552228157 -0.526974209 -0.521835543 -0.536568007 -0.536564655 -0.533739402 -0.536517444
Data Y:
0.0142377 0.05948486 0.1525919 0.12065245 0.00982269 -0.03951274 -0.00147403 0.03059889 0.10436959 0.08331938 -0.01716591 0.01109873 -0.01768092 -0.02931767 -0.06896155 -0.08861504 -0.08324867 -0.05371193 0.06273226 0.07767516 0.06579092 0.05516475 0.05925245 0.08543882 0.09550461 0.08896114 0.07296073 0.0845536 0.10957533 0.10009183 0.06547486 0.05005369 0.04102925 0.03095616 -0.01776122 0.00992901 -0.00692717 -0.0119645 -0.0060741 -0.04384874 0.04100349 0.0704824 0.03940004 0.05244081 0.08466181 0.04539119 0.00405616 0.08533605 0.06064081 0.01054517 0.02504058 0.01554287 -0.00581619 -0.08928089 -0.05639107 -0.04552528 -0.06380895 -0.07245358 -0.0661626 -0.06886088
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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