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Data X:
-9.025408898 0.961051813 -0.763484335 -1.03592439 2.248061689 -0.848089637 -4.983828298 0.25823367 -6.879841767 -6.638261166 0.217477947 -0.810495567 -10.47131954 0.209299231 -1.704377914 2.62868046 4.578783287 1.179951675 -0.727402164 4.535347277 -2.951113434 1.060226936 2.350536321 3.393009597 -5.868982764 1.957546649 4.794110187 2.330673725 3.685793615 3.979608164 0.265243998 6.254041485 0.521670132 1.201464026 4.406962455 7.330398012 -4.44210984 2.078921143 5.999608617 4.262563712 4.255415527 5.171085938 3.762563712 7.433697522 3.320983111 0.95204822 4.243525993 7.964281264 -2.961628926 3.265725365 4.685931471 -3.114549896 -0.703347383 -6.424721877 -9.75929215 -7.222247245 -9.551113434 -11.50520279 -7.029257573 -2.322522958
Data Y:
34359.65199 38587.02116 39828.34883 25986.36384 23275.05495 17536.29032 18772.05119 17652.20376 13809.9006 8724.299812 16880.69725 30459.84012 46817.26404 48434.47313 33761.22827 23046.26404 19412.02669 18194.0587 16429.72728 14460.31681 6857.947638 8866.128469 13765.73302 26895.93617 44300.32807 40044.92511 20984.05693 7217.188746 -3365.781217 -1398.080623 -6766.60414 -11243.17094 -18608.92805 -24943.61165 -24305.5909 -4494.039323 13943.06444 -1778.359277 -9378.922319 -23034.8075 -28900.61363 -22818.44406 -26936.8075 -37226.46857 -33849.20671 -46097.09564 -37418.45908 -19433.11086 -7315.340504 -16251.85078 -27402.16718 -37091.92054 -36045.35375 -31317.06936 -28183.27647 -25545.39129 -29559.05236 -36135.66442 -24894.58339 -7562.619362
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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