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Data:
-2.250815803 -2.250025575 -2.248469388 -2.249602446 -2.248990826 -2.24598369 -2.245779817 -2.245380711 -2.243004552 -2.245 -2.244359233 -2.247455919 -2.248922457 -2.248721805 -2.24955 -2.246140089 -2.244470821 -2.245559389 -2.246977887 -2.246879607 -2.248921569 -2.248486036 -2.249574156 -2.249339853 -2.245839844 -2.247176987 -2.247019932 -2.251234867 -2.253571774 -2.255750845 -2.253840231 -2.253942308 -2.253956835 -2.253815916 -2.254736842 -2.253448111 -2.254229852 -2.251706387 -2.251615055 -2.252952381 -2.255066414 -2.252336802 -2.252961738 -2.251556604 -2.251517436 -2.252561205 -2.251263504 -2.251846298 -2.252559663 -2.25411215 -2.254727018 -2.251061453 -2.247860465 -2.249532191 -2.248863216 -2.249580452 -2.250653775 -2.246850575 -2.248297384 -2.24959193 -2.249661482 -2.248259479 -2.246000912 -2.247477314 -2.248637392 -2.247013575 -2.245843102 -2.245990991 -2.245778578 -2.248898876 -2.248470166 -2.247046168
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
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R Server
Big Analytics Cloud Computing Center
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