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Data X:
735.07 -1226.348 811.434 824.888 421.362 -513.422 -190.064 -196.224 548.168 603.85 304.79 120.216 602.984 -1070.538 895.432 615.108 140.41 -1028.07 -762.444 -245.956 -119.224 -216.468 655.79 785.424 761.536 -1075.126 798.71 649.59 547.884 -485.194 185.812 317.828 1063.094 339.618 288.61 1020.778 394.24 -273.966 573.402 556.436 -219.1 -1589.666 -868.892 508.342 -407.442 2.922 160.734 249.968 116.214 -1918.548 -262.954 -457.512 -1736.924 -1853.188 -1579.46 -752.802 -598.48 -292.484 -232.932 -245.918 494.592
Data Y:
-3.041 -30.8449 -73.4388 -27.0621 -0.7944 -67.9576 -17.8417 -64.8297 -65.2931 -13.417 22.335 4.5873 15.8937 37.4506 -31.5559 19.8439 21.801 -10.213 35.3443 -31.1783 -6.1197 35.5541 -1.42 25.7907 11.8533 -5.8368 -34.609 15.54 18.5837 27.0118 -6.8619 -4.8801 26.2342 70.4244 27.461 29.7524 34.0675 38.1812 -10.1124 2.7433 31.2555 -0.2038 18.2439 10.9496 -13.5786 9.2486 111.4112 16.1069 36.6952 54.7651 -49.9012 26.4429 28.9053 14.0231 36.6025 -56.4916 11.3715 65.1273 192.7919 87.0766 136.3671
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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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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