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Data:
61.04 64.21 63.92 68.48 67.76 65.37 61.84 59.88 62.91 63.67 59.96 62.80 64.26 66.35 67.43 69.45 72.98 71.58 69.97 71.93 68.53 71.29 72.75 71.64 69.97 70.78 73.52 73.86 76.80 74.57 73.36 74.77 74.35 71.14 72.51 69.19 66.25 63.33 60.55 62.91 59.76 58.57 59.33 60.75 59.05 59.59 58.97 59.24 63.28 62.03 63.43 62.41 61.05 56.31 53.30 51.99 55.42 59.02 59.89 59.39 61.44 61.64 59.69 57.11 62.28 65.87 64.28 63.63 64.11 66.46 61.93 62.37 64.94 65.20 65.08 64.76 68.00 69.14 70.68 72.81 73.93 75.79 77.02 75.48 71.47 71.98 71.09 74.04 76.70 79.10 81.62 81.66 81.22 83.69 88.60 91.86 95.93 96.32 93.84 98.18 88.71 88.28 91.27 93.31 96.00 95.98 97.91 92.69 90.57 90.71 88.96 91.77 95.50 98.81 01.84 05.15 10.21 01.84 05.62 06.23 10.14 16.69 18.52 16.32 25.96 26.29 32.19 27.35 38.54 34.86 35.36 40.21 45.29 45.08 28.88 23.26 25.10 15.20 13.77 14.59 15.46 06.23 01.18 04.55 06.89 93.88 77.70 71.85 64.15 67.81 61.04 57.04 49.93 54.43 40.81 46.28 42.36 37.71 44.60 46.34 40.83 36.51 46.47 41.68 40.17 37.51 40.03 44.76 45.52 46.25 52.07 52.38 52.51 52.24 50.33 51.55 53.20 58.63 56.34 61.67 66.31 68.44 72.04 69.55 69.16 65.63 59.89 63.56 68.05 69.45 70.93 67.51 73.89 72.74 68.02 69.29 72.04 66.02 69.95 71.77 78.53 80.50 77.00 77.43 76.35 77.47 76.05 75.47 69.87 73.36 78.05 79.36 82.75 78.00 74.54 72.89 71.19 74.13 79.81 79.66 81.50 81.24 80.68 80.00 84.87 84.92 83.24 85.12 86.15 75.11 71.61 70.04 73.97 71.51 73.78 77.18 78.86 72.14 76.09 76.01 78.98 78.95 80.70 75.39 73.82 75.17 74.60 76.45 73.66 76.49 81.58 82.66 81.25 81.69 81.43 86.85 84.88 81.98 83.76 89.19 87.79 88.02 91.51 91.38 88.03 91.54 89.11 89.34 89.03 85.58 86.20 97.88 04.42 01.16 01.07 05.40 07.94 12.79 09.66 12.29 13.93 97.18 99.65 00.10 00.59 00.22 99.29 93.01 91.16 94.94 96.20 97.24 99.87 95.70 86.88 85.38 82.26 85.37 86.45 87.24 87.96 79.85 79.20 82.98 86.80 87.40 93.32 94.26 98.99
Sample Range:
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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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Summary of computational transaction
Raw Input
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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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