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Data X:
5877.641004 5264.324975 6142.177029 10268.13606 10473.95003 11975.11389 27071.77554 39415.43061 17684.58436 18056.32275 14220.73908 19910.88099 20825.80839 17078.14492 15893.85256 16587.08554 15452.75508 16634.15379 30075.88387 30024.98807 10837.18097 18212.88846 9612.37698 15383.76942 -10793.78215 -2665.770597 -2747.627613 5616.223003 3604.418271 -2472.739559 1060.469578 -8354.360115 -19737.63012 -29682.41175 -31450.81059 -26654.75529 -33207.92652 -38530.07447 -28833.33473 -39506.72592 -28597.11427 -2341.826355 343.2037971 -13047.16234 -26584.87934 -26927.22357 -18923.29632 -13025.37249 -24270.05651 -29451.89576 -10651.68425 -13617.95194 -4687.142289 1547.342007 -3588.856605 -9350.202187 -17243.26871 -6501.430206 -6826.935843 600.2497751 5685.935602 7979.577494 10909.68967 7336.861697 15319.24875 23453.89399 18322.6577 15060.75058 10453.76214
Data Y:
12759.67629 10622.97664 10308.72729 14324.40815 14766.20241 15482.80982 32045.46369 47967.4267 16954.41759 19078.51507 16119.42199 22381.18044 23681.8785 17447.24575 16518.34184 18164.67245 16311.81215 18389.41422 32616.54318 37136.81187 8887.473886 15353.85271 8311.578885 13271.94069 -12610.00173 -5753.20383 -6392.730644 4072.838634 97.67948377 -3302.437027 -349.966368 -9077.38537 -22399.95763 -30889.52098 -29794.84033 -25229.06177 -31107.64024 -36194.88959 -27783.31195 -36208.22571 -26169.46189 -2433.81936 -324.3648547 -13694.31753 -27975.766 -28540.55489 -20562.5741 -14825.48688 -24696.80327 -27729.30797 -9923.327593 -12574.73706 -3445.486919 2484.396362 -2379.636843 -8368.905883 -16495.70087 -8069.129444 -8234.645685 -1098.922628 3114.041771 4665.292196 6553.747945 1644.27573 11190.37869 17827.49059 13036.98367 8499.203837 2547.001736
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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