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Data:
0.00129909929391305 0.0399953455650052 -0.0388246377373741 -0.00331410653299091 0.0210839113108800 -0.0306161034410643 -0.0177106810085845 -0.046387990142741 0.000293807560611557 0.0283994201318544 -0.0097276499256617 -0.0226399010542774 -0.0154224216079923 0.0180996287729906 0.0174136599175999 -0.0230868312646511 0.0152995239008014 0.0186909303105856 0.0411546583121751 -0.0309853409627296 0.00641105220624505 0.0159182504768269 -0.0129464581053229 -0.0128078454602796 0.0274724628079561 0.0283118917490450 -0.0263638289790966 0.00959383292935723 0.0166833770244468 0.0265094201387677 -0.00109417116631749 -0.0125243883301391 0.0328788388222352 -0.0150708239891775 0.0280916856622302 0.0249707612360408 0.0417384790369306 -0.0189545400438149 0.0134272541571829 0.00114937541706439 0.0792737906675707 0.00631274994392772 -0.0258498505131595 0.00309104687364825 0.0263272745307186 -0.0872423105882159 -0.0367158144235664 -0.0859756758601653 -0.027777298319539 0.0830853071279365 -0.0362488888752577 -0.0402967807676649 0.0486619532670178 0.00786966021276925 0.0390206657243493 0.0258356960136144 0.00122924684045933 0.00419954182511484 0.0191498676670216 0.00542117110649887 -0.00117174374524698
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
R Code
par1 <- as.numeric(par1) par2 <- as.numeric(par2) x <- as.ts(x) library(lattice) bitmap(file='pic1.png') plot(x,type='l',main='Run Sequence Plot',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic2.png') hist(x) grid() dev.off() bitmap(file='pic3.png') if (par1 > 0) { densityplot(~x,col='black',main=paste('Density Plot bw = ',par1),bw=par1) } else { densityplot(~x,col='black',main='Density Plot') } dev.off() bitmap(file='pic4.png') qqnorm(x) qqline(x) grid() dev.off() if (par2 > 0) { bitmap(file='lagplot1.png') dum <- cbind(lag(x,k=1),x) dum dum1 <- dum[2:length(x),] dum1 z <- as.data.frame(dum1) z plot(z,main='Lag plot (k=1), lowess, and regression line') lines(lowess(z)) abline(lm(z)) dev.off() if (par2 > 1) { bitmap(file='lagplotpar2.png') dum <- cbind(lag(x,k=par2),x) dum dum1 <- dum[(par2+1):length(x),] dum1 z <- as.data.frame(dum1) z mylagtitle <- 'Lag plot (k=' mylagtitle <- paste(mylagtitle,par2,sep='') mylagtitle <- paste(mylagtitle,'), and lowess',sep='') plot(z,main=mylagtitle) lines(lowess(z)) dev.off() } bitmap(file='pic5.png') acf(x,lag.max=par2,main='Autocorrelation Function') grid() dev.off() } summary(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Descriptive Statistics',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'# observations',header=TRUE) a<-table.element(a,length(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'minimum',header=TRUE) a<-table.element(a,min(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q1',header=TRUE) a<-table.element(a,quantile(x,0.25)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q3',header=TRUE) a<-table.element(a,quantile(x,0.75)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'maximum',header=TRUE) a<-table.element(a,max(x)) 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
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R Server
Big Analytics Cloud Computing Center
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