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Data:
0.00 0.91 0.74 11.74 19.90 26.77 23.42 27.86 27.69 34.12 15.35 0.65 8.98 16.83 16.16 18.91 21.80 24.98 32.07 23.12 25.50 21.19 26.70 21.78 33.04 45.41 61.55 50.24 65.51 72.17 70.44 65.69 60.25 62.31 70.48 59.73 66.68 51.51 44.46 43.64 24.83 19.80 28.22 24.97 13.84 10.17 0.60 -17.28 -12.31 -12.14 -15.49 -16.70 -17.62 -11.45 -21.71 -28.00 -44.11 -54.76 -53.32 -74.29 -62.78 -62.86 -78.74 -83.31 -86.54 -92.44 -85.10 -87.44 -87.17 -81.37 -80.09 -87.23 -80.88 -82.93 -82.43 -79.69 -77.21 -83.69 -83.13 -85.59 -88.00 -88.56 -86.82 -89.51 -88.74 -90.44 -90.19 -90.47 -87.50 -90.17 -94.16 -91.67 -106.39 -102.77 -99.88 -97.77 -102.14 -101.64 -105.13 -99.01 -97.59 -97.65 -101.12 -109.59 -111.95 -106.19 -98.80 -102.68 -96.07 -102.28 -108.71 -101.48 -104.53 -106.94 -101.89 -100.37 -104.90 -109.43 -104.06 -107.85 -102.33 -110.65 -117.22 -132.60 -130.09 -141.03 -130.06 -134.47 -149.17 -143.39 -138.20 -156.80 -171.42 -180.18 -187.92 -197.15 -206.14 -206.31 -202.25 -199.91 -208.24 -199.96 -196.32 -198.68 -204.45
Sample Range:
(leave blank to include all observations)
From:
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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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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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