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Data X:
335.2807094 -6315.156455 -8630.36 7249.484254 3022.609926 6452.735598 3829.376307 -360.9351859 4232.268359 -4860.450223 -4137.887387 -3268.121007 -3195.19888 -4482.480298 -12291.55817 8975.80112 6572.597575 11656.83119 4297.112613 3942.986941 926.0648141 -4589.216604 -5380.77944 -4466.342276 -1629.54582 -5233.186529 -13266.90511 8499.45418 3926.45418 7970.298433 3178.298433 2400.579851 3087.939142 -2262.701567 -3992.701567 -2256.701567 2104.657724 -2847.982984 -9914.623693 8904.017016 7430.298433 7357.017016 9309.45418 3135.939142 4144.939142 -2513.138731 -4901.060858 -2141.982984 -200.1387307 -7155.498022 -11218.49802 2728.861269 1390.579851 5086.579851 3458.142687 -2174.060858 87.65772447 -3633.982984 -5709.701567 -2663.420149
Data Y:
-97.0413027 -338.0413544 138.4587102 517.4586327 -277.5414708 -120.5415742 -305.0415871 -253.0417423 439.458193 110.4581672 858.4581155 519.9579991 -967.5420397 -129.5420138 57.95794738 -375.5420397 -542.041975 874.4581413 834.4581155 299.4582189 1419.958258 260.9582836 803.9583353 1090.958387 229.4584516 360.9584646 601.9584387 909.4584516 -243.5415484 118.4583741 229.4583741 -326.5416518 589.9583611 -301.5416259 -385.5416259 596.4583741 -187.041613 110.4583999 -639.0415871 1058.4584 -259.5416259 -637.5416001 4.45845164 299.9583611 -117.0416389 -15.54167766 -420.0416389 326.4583999 -670.5416777 -811.0416906 -199.0416906 -562.5416777 -445.5416518 242.4583482 -1460.541704 -941.0416389 -584.041613 -289.5416001 -643.5416259 -358.5416518
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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Computing time
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R Server
Big Analytics Cloud Computing Center
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