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Data X:
-4509.6 -4514.6 -4504.6 -4534.6 -4266.6 -4477.6 -4529.6 -4349.6 -4432.6 -4476.6 -4420.6 -4505.6 -4521.6 -4507.6 -4521.6 -4480.6 -4533.6 -4509.5 -4506.5 -4497.5 -4404.5 -4496.5 -4444.5 -4440.5 -4412.5 -4527.4 -4513.4 -4450.4 -4501.4 -4483.4 -4449.4 -4520.4 -4504.4 -4486.4 -4428.3 -4463.3 -4499.3 -4470.3 -4416.3 -4510.3 -4473.4 -4510.3 -4450.3 -4489.3 -4438.3 -4457.3 -4468.3 -4352.3 -4501.3 -4503.4 -4491.5 -4530.6 -4410.6 -4506.6 -4483.7 -4444.7 -4422.7 -4505.7 -4475.7 -4370.7
Data Y:
-657.60 -820.59 -441.59 54.41 -583.60 -271.60 -436.60 -150.60 639.40 349.40 1175.40 1012.40 -416.59 382.42 628.44 177.44 -88.55 1152.46 1151.48 460.48 1522.49 324.51 789.51 998.53 39.54 151.56 431.57 719.58 -433.41 45.59 156.60 -360.39 536.62 -374.37 -458.35 523.68 -279.32 -1.32 -770.31 946.67 -332.35 -749.35 -185.32 246.69 -170.31 -10.29 -473.30 214.70 -665.26 -786.45 -17453 -557.57 -479.61 208.35 -141.68 -994.71 -676.72 -401.72 -716.72 -392.72
Sample Range:
(leave blank to include all observations)
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bandwidth of density plot
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# lags (autocorrelation function)
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36
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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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