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Data:
305687 305115 280379 280039 274949 264528 257662 254599 253056 245478 245107 244909 243180 242153 236316 234863 220835 213487 213310 209631 208823 201748 201603 201409 197067 197033 193662 192887 191467 190729 189764 189066 187289 185366 185288 185279 183260 183059 182557 181853 179571 176577 175663 173587 173260 170635 170588 169613 169569 169093 168059 167255 167226 166142 161729 160905 157566 156990 155012 154730 152366 152193 148857 145908 145120 144530 143937 142339 142286 141933 141150 139409 139144 137544 135306 134088 132798 131337 131108 130539 130533 130413 129796 129340 129100 128873 128768 128734 128274 128075 127930 127394 127185 126630 125927 121976 121630 120362 118807 117805 115911 115885 113450 113337 112004 109237 108715 107434 106888 106351 106193 105477 102350 101324 98791 98466 98066 96981 96634 93125 91185 90961 90938 89882 89318 89059 86621 81530 81106 80964 80953 78800 76470 75746 75032 74112 73567 71908 69471 67507 65029 62731 61857 50999 46660 43287 38214 35523 32750 31414 24188 22938 21054 17547 14688 7199 969 455 203 98 0 0 0 0
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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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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