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Data X:
-0.652 -0.818 -0.542 -0.58 -0.74 -0.448 -0.64 -0.754 -1.12 -1.292 -0.586 0.092 -0.246 -0.12 -0.42 -0.632 0.258 -0.022 -0.266 -0.324 0.1 0.786 0.554 0.304 0.508 0.874 0.892 1.026 0.276 0.238 0.498 0.082 -0.18 -1.026 -0.678 -0.586 -0.732 -1.116 -0.954 -1.376 -1.47 -1.118 -0.92 -0.822 -0.73 -0.746 -0.78 -1.202 -1.186 -1.136 -1.464 -0.99 -0.2 0.542 0.68 1.062 1.128 1.962 1.632 2.83 3.336 3.566 3.076 3.062 2.466 1.084 0.76 0.732 0.48 -0.74 -0.718 -1.712 -2.406
Data Y:
-0.294 0.394 0.486 0.47 0.49 0.494 0.67 0.982 0.87 0.356 -0.472 -0.776 -0.572 0.82 1.27 1.276 0.696 0.206 0.318 0.502 0.64 0.602 0.328 0.228 -0.024 0.708 0.824 0.852 0.632 0.486 0.566 0.714 0.71 0.558 0.484 0.238 -0.004 0.158 0.102 0.098 -0.03 -0.106 -0.09 0.036 0.03 -0.092 0.01 -0.264 -0.762 -0.472 -0.698 -0.97 -0.95 -0.936 -0.74 -0.636 -0.874 -1.146 -1.576 -1.83 -1.458 -0.218 -0.008 -0.436 -0.988 -1.222 -0.86 0.034 0.38 0.41 0.124 -0.284 -0.172
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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