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Data:
0.197299870124694 -7.4891834722532 -2.46357571004573 -11.1352144478093 -8.30666563148338 2.52543893701216 -9.07701600470547 6.13368551812671 -2.75736870709027 6.27193132285353 -4.86579008662195 -16.1915786204687 -6.04877252914152 -16.7022801433001 -12.2750854582395 11.9019305464657 8.86105500160429 -23.4303488204468 4.62806867714669 -9.0040358913486 -4.57543505507405 -1.10614123623148 -20.6385954015612 -14.4684198267564 -3.99999999999997 -4.25613735429343 12.7228091968775 -12.3192977007806 5.36140459843875 6.29824425195156 0.212282472462960 -17.6807022992194 1.63859540156125 5.34035114960969 -14.1070152283177 0.489473275585482 -4.85087787402421 14.8929847716824 -9.17017557480486 14.6807022992194 -30.0421068976581 -4.46841982675639 -6.38245804726782 3.76491609453564 4.02105344882906 0.680702299219377 9.17017557480483 12.4894732755855 -2 -14.5315801732436 -0.212282472462960 -11.6596488503903 3.21228247246296 19.6596488503903 7.04210689765813 -8.17017557480484 6.59648850390312
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) 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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