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Data X:
100 97.82226485 94.04971502 91.12460521 93.13202153 93.88342812 92.55349954 94.43494835 96.25017563 100.4355715 101.5036685 99.39789728 99.68990733 101.6895041 103.6652759 103.0532766 100.9500712 102.345366 101.6472299 99.56809393 95.67727392 96.58494865 96.32604937 95.37109101 96.00056203 96.88367859 94.85280372 92.46943974 93.99180173 93.45262168 92.26698759 90.39653498 90.43001228 91.04995327 89.07845784 89.69314509 87.92459054 85.8789319 83.20612366 83.85722053 83.01393462 82.84508195 78.68864276 77.56959675 78.53689529 78.55717715 77.4761291 81.58931659 85.02428326 91.71290159 95.96293061 90.84689022 92.28788036 95.56511274 93.62452884 92.63071726 89.50914211 87.17171779 86.72624975 85.63212844
Data Y:
100 96.21064363 96.31280765 107.1793443 114.9066592 92.56060184 114.9995356 107.1236185 117.7765394 107.3650971 106.2970187 114.5072908 98.0031578 103.0649206 100.2879168 104.6066685 111.1544534 104.9874617 109.9284852 111.5352466 132.4974459 100.3436426 123.0983561 114.2379493 104.569518 109.0833101 106.9843039 133.6769759 124.8537197 122.5132349 116.8013374 116.0118882 129.7575926 125.1973623 143.7912139 127.9465032 130.2962757 108.4424631 129.3675118 143.6797622 131.8844618 117.6186496 118.9560695 104.8202842 134.624315 140.401226 143.8005015 153.4317823 153.2924677 127.3149438 153.5525216 136.9276493 131.7730101 144.3391845 107.4208229 113.6249652 124.2221603 102.0618557 96.36853348 111.6838488
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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R Server
Big Analytics Cloud Computing Center
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