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Data:
127269 75620 88255 104300 53891 23637 239665 26847 82376 108063 130696 106111 77157 156938 111186 193991 137623 129655 90067 118206 128389 226536 67073 89947 101451 121691 147649 101001 88745 145509 158310 82934 144300 50968 169102 129402 197808 102540 76806 135028 158063 97980 99862 49417 79864 238236 66613 133589 179955 104416 88737 24019 178249 64672 85913 149157 136059 147863 157786 97096 194551 166067 107928 136136 105283 74153 95612 108093 118089 51000 97034 52125 96331 106760 82657 159858 161402 90287 74853 87661 85840 224167 107905 82275 80953 90496 67181 155920 124542 84443 93028 106264 84922 132246 145658 106443 108558 138044 136773 183992 114968 126632 80456 39948 108674 101041 114400 153398 57427 78870 127197 119023 20764 99305 61675 72554 168643 21054 151340 23175 157461 103303 48355 51536 38214 86725 159468 90604 183334 137626 204060 114015 51227 147342 210790 41227 198679 81901 130930 82730 50656 195126 115032 173260 144766 57297 112567 142346 0 14688 98 455 0 0 111354 148268 0 203 7199 46660 17547 73567 969 76925
Sample Range:
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To:
bandwidth of density plot
(?)
# 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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R Server
Big Analytics Cloud Computing Center
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