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Data:
4.62 4.54 3.99 3.83 3.73 3.86 4.44 5.43 5.28 5.44 5.37 5.4 5.16 5.23 5.07 4.99 5.21 5.62 5.92 6.01 6.58 6.78 6.97 6.9 7.28 7.2 7.29 7.09 6.84 6.54 6.89 7.76 7.74 7.98 7.91 7.94 7.92 7.88 7.76 7.59 7.72 7.73 8.31 8.72 9.01 8.88 8.53 8.44 8.04 8.02 7.67 7.46 7.3 7.2 7.38 7.88 7.83 7.14 7.04 6.77 6.89 7.22 7.54 7.54 7.12 6.96 7.21 7.85 8.18 8.3 7.98 8.25 9.08 8.66 8.28 7.69 7.14 7.31 8.17 9.36 9.08 8.74 8.62 8.51 8.15 8.02 7.67 7.53 7.66 7.56 7.85 7.79 7.21 6.8 6.27 5.76 5.71 5.25 4.54 4.66 4.24 3.55 4.01 4.42 3.74 4.03 3.7 4.11 4.1 3.85 4.01 3.51 3.16 3.07 3.55 3.73 4.54 5.15 5.37 5.42 4.7 4.77 4.63 5.29 5.57 5.92 6.22 6.34 6.54 6.71 7 6.83 7.09 6.46 6.24 6.42 6.56 5.98 6.81 6.61 6.6 6.82 6.54 6.86 7.31 7.54 7.17 5.58 4.59 5.14 6.39 7.04 7.27 5.84 5.65 6.03 6.24 6.03 5.43 5.44 5.59 5.03 5.46 5.59 5.54 6.03 5.83 5.61 6.07 6.32 6.91 6.54 6.11 6.13 6.6 6.47 6.88 6.79 6.41 6.26
Sample Range:
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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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R Server
Big Analytics Cloud Computing Center
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