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Data:
0.000816495986064032 -0.0410329790889227 0.0101081992594331 -0.0360798110911782 -0.0563432727052785 -0.0142183277305241 -0.0298052633325197 -0.0602942433388665 0.0145527194433094 0.00367243539668562 0.0239313164299128 0.00603903744694586 0.0196650209507765 -0.00554984596295429 -0.00498694306016242 0.00815491699717673 0.0567902270440178 0.0143312031557586 0.0741604805929497 -0.0133803979618741 -0.045833752309627 0.0170913480004510 -0.119743603166854 -0.047258986198743 -0.00422550286539092 0.08407727862222 -0.0946114581379 -0.0337013395843897 0.0766087188610801 0.00451311933236909 -0.0260799360406518 -0.0258397586422158 0.0395455475475366 0.0864801984092718 0.0335536914394249 -0.0654807605873451 0.0485688401176023 0.0286107744350892 0.0972226583801824 -0.111757800037146 -0.00651122741554178 -0.0744367847698600 -0.0916911861910863 0.0221447173828979 -0.0094130033839226 -0.0518466432349798 -0.0192782746495473 -0.0203555382811873 0.0192986311877937 -0.0554818928154829 0.0618149207262586 0.0646289188191846 -0.0185318681379408 -0.0385004545073152 0.0067253003069302 -0.00441392504770799 0.00499720959127403 0.117033549693058 0.0297066687489206 -0.0325086186512087 0.0970109130719323
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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