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Data X:
3.04 3.12 3.21 3.34 3.45 3.74 4.02 4.24 4.87 5.62 6.02 5.98 5.89 5.76 5.58 5.39 5.19 5.16 5.2 5.25 5.26 5.21 5.18 5.13 5.03 5.01 4.87 4.86 4.82 4.69 4.65 4.61 4.47 4.37 4.29 4.2 4.19 4.09 3.88 3.87 3.74 3.61 3.43 3.29 3.18 3.07 3.02 2.97 2.98 3.01 3.06 3.12 3.16 3.19 3.21 3.27 3.36 3.45 3.52 3.58
Data Y:
-0.355434285 -0.342738227 -0.337614889 -0.311154064 -0.276874024 -0.266202421 -0.245687006 -0.280582004 -0.296319266 -0.241532853 -0.286831767 -0.362557929 -0.403796501 -0.455524953 -0.441668099 -0.441926312 -0.454319274 -0.439995996 -0.388522449 -0.38648635 -0.376379233 -0.384173883 -0.352556294 -0.329015309 -0.309100484 -0.3159773 -0.294086537 -0.300918624 -0.301288893 -0.280808417 -0.268040242 -0.262287267 -0.278616621 -0.253168575 -0.231983761 -0.241140784 -0.247719327 -0.237756046 -0.235071912 -0.244514032 -0.204653059 -0.183986542 -0.177141795 -0.19086878 -0.170248728 -0.164327623 -0.183570737 -0.203430389 -0.206363871 -0.18539989 -0.195978388 -0.238544032 -0.25758361 -0.27770798 -0.263440944 -0.271476757 -0.293266972 -0.261671305 -0.222342622 -0.200324644
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
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R Server
Big Analytics Cloud Computing Center
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