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Data:
110.089 99.966 94.195 119.588 125.946 118.906 108.717 118.357 115.422 130.937 111.802 120.357 121.12 108.752 98.973 116.721 123.857 114.056 98.309 110.251 108.538 122.526 118.394 116.691 116.014 111.784 95.164 121.028 129.89 116.102 102.055 113.562 113.071 126.486 119.472 117.141 121.925 112.688 90.974 126.398 130.401 116.873 111.917 113.919 117.931 139.332 127.781 118.103 136.984 119.566 107.238 139.389 139.798 138.074 129.739 125.098 129.341 149.083 137.721 130.126 140.499 118.165 115.932 144.662 136.159 147.339 138.807 135.275 135.84 161.702 132.606 147.419 154.865 131.545 126.212 150.316 154.524 154.28 131.059 147.168 141.8 162.022 143.924 151.406 159.601 143.513 132.302 152.021 171.573 161.591 134.057 172.247 173.384 173.706 188.178 165.932 179.795
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) 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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