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Data:
0.00249999703970397 -0.0649826118455392 0.0275459792715598 -0.208071605124589 -0.205976756595902 -0.0935347183653828 -0.050233446319992 -0.00988797955273081 -0.180572493276974 -0.132637616997870 0.159982297044476 -0.165395832107720 0.0338705347448762 -0.105439218110932 0.287392187884027 -0.122431040183128 -0.0855362947771189 -0.00109230629519701 -0.228261862611870 -0.0302492455292581 -0.0626310087654128 -0.0763606127993333 0.00968773912133767 0.176659169085792 0.0147152647275133 -0.0343398076314363 0.172497318029791 0.0805909794619493 -0.0356538336252446 -0.044675717305918 -0.162539592727164 -0.0209701623970107 0.0421864375592211 0.173870426922868 -0.007940212082814 -0.268495283233181 0.224592887452782 0.143387493119256 -0.0354507223655091 0.178470155660242 0.0368782754940081 -0.165801514016751 0.351883066457688 0.272401448772026 0.104796183541335 -0.160180311677687 -0.0398217449186744 -0.157925307679901 -0.00270252679334952 -0.272814380729499 -0.0309052966524012 -0.127184288801741 0.258848765649000 -0.0554248461628695 -0.0344273166153885 0.140358813011808 -0.103212753316634 0.249045074754824 0.0638715022539165 -0.0387202808279945 0.198755593507467
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
0 seconds
R Server
Big Analytics Cloud Computing Center
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