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Data X:
-7887.38628 -8153.249971 -8050.245702 -7820.43309 -7961.598309 -7877.474807 -7781.108569 -7891.555768 -7847.376918 -7683.962074 -7692.226978 -7972.697994 -8108.607671 -8343.945823 -8250.612764 -8239.157028 -8155.088873 -8234.545434 -7982.266075 -8149.727729 -8170.722635 -8101.449194 -8179.134035 -8421.929572 -8617.979002 -8766.284799 -8618.868306 -8608.777983 -8748.581233 -8692.242257 -8515.081307 -8576.701438 -8642.645266 -8530.422903 -8659.69717 -8624.979149 -8743.290039 -8905.048128 -8742.865833 -8725.697994 -8765.611115 -8648.052397 -8673.760231 -8610.19215 -8534.813106 -8483.389724 -8580.503864 -8700.645266 -8816.079659 -8924.674177 -8917.935636 -8883.476455 -8807.16639 -8829.066705 -8768.618682 -8721.75499 -8748.015626 -8776.99855 -8954.624599 -9053.98065
Data Y:
-26899.91791 -27221.72575 -27317.12474 -27344.50896 -27823.97196 -27724.58281 -27255.01638 -27091.98191 -26630.7997 -26910.7898 -26887.88832 -27413.60748 -27971.09017 -28096.30197 -28082.60737 -28558.43982 -28738.84374 -28804.92749 -28397.19356 -28720.79451 -28500.2773 -28755.97677 -28718.6024 -29299.81415 -28936.17381 -28881.42998 -28321.58768 -28861.07037 -28646.56793 -28114.43993 -27536.57794 -27082.29229 -26368.58303 -26969.47456 -27154.69128 -26624.19383 -26836.9672 -26906.70611 -26991.83909 -27604.60748 -27551.77498 -26686.30711 -26767.77016 -25811.18409 -25771.81463 -26344.60272 -26401.87366 -26360.58303 -26672.74555 -27176.85386 -27699.26757 -28752.41521 -28974.55803 -29436.92251 -29195.04078 -28833.23294 -28995.73045 -29580.32643 -29882.47418 -29891.00621
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')
Compute
Summary of computational transaction
Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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