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Data:
26 57 37 67 43 52 52 43 84 67 49 70 52 58 68 62 43 56 56 74 65 63 58 57 63 53 57 51 64 53 29 54 58 43 51 53 54 56 61 47 39 48 50 35 30 68 49 61 67 47 56 50 43 67 62 57 41 54 45 48 61 56 41 43 53 44 66 58 46 37 51 51 56 66 37 42 38 66 34 53 49 55 49 59 40 58 60 63 56 54 52 34 69 32 48 67 58 57 42 64 58 66 26 61 52 51 55 50 60 56 63 61 52 16 46 56 52 55 50 59 60 52 44 67 52 55 37 54 72 51 48 60 50 63 33 67 46 54 59 61 33 47 69 52 55 41 73 52 50 51 60 56 56 29 66 66 73 55 64 40 46 58 43 61 51 50 52 54 66 61 80 51 56 56 56 53 47 25 47 46 50 39 51 58 35 58 60 62 63 53 46 67 59 64 38 50 48 48 47 66 47 63 58 44 51 43 55 38 45 50 54 57 60 55 56 49 37 59 46 51 58 64 53 48 51 47 59 62 62 51 64 52 67 50 54 58 56 63 31 65 71 50 57 47 47 57 43 41 63 63 56 51 50 22 41 59 56 66 53 42 52 54 44 62 53 50 36 76 66 62 59 47 55 58 60 44 57 45
Sample Range:
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bandwidth of density plot
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# lags (autocorrelation function)
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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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