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Data:
0.084299366 -15.56921248 -6.995361993 -2.07575919 6.064721852 3.100631839 -7.278726041 11.93055924 -15.18009268 -4.969659576 -3.061843327 5.178764132 -2.296388145 -1.858532578 -8.746378956 -8.02346934 4.803199996 3.901735267 -11.30690803 4.262250402 -6.886280101 4.127978964 4.248249289 -5.918115474 -2.621275417 -5.119476515 -6.191692926 1.576828301 6.933818889 1.304353306 0.701451547 18.14876933 -13.62519621 -8.968419894 -3.480244165 0.133268756 0.156896176 -1.284121305 -8.458697235 -2.915182784 0.150465579 3.868779877 7.709937971 -4.116509763 -2.744758527 3.192868109 -6.221202771 1.254893558 4.23585013 0.153440583 -2.057190033 2.144228696 -1.681562156 5.031845095 2.248233111 -6.583725737 -2.854201769 5.037975261 4.437112087 -0.675511402 -2.506847023 2.359094484 -6.318494293 -3.819498628 2.173071182 4.136639862 -6.962296546 5.280086019 4.277455899
Sample Range:
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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) grid() dev.off() if (par2 > 0) { bitmap(file='lagplot.png') dum <- cbind(lag(x,k=1),x) dum dum1 <- dum[2:length(x),] dum1 z <- as.data.frame(dum1) z plot(z,main=paste('Lag plot, lowess, and regression line')) lines(lowess(z)) abline(lm(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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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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