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Data:
-0.00027027 -0.007210884 -0.02375 -0.044935065 -0.066666667 -0.063870968 -0.085960265 0.037094017 -0.084294479 -0.045868263 -0.04 0.02 -0.00739726 -0.025751634 -0.019106145 -0.04097561 -0.051428571 -0.002346369 -0.068050314 0.055971223 -0.04741573 -0.047039106 -0.025977011 0.031976048 0.00125 0.007951807 -0.016649215 -0.030561798 -0.020697674 0.003870968 -0.053619632 0.059735099 -0.037291667 -0.030847458 0.009528796 0.075555556 0.054285714 0.02 0.038957346 0.014186047 -0.016082474 -0.02040404 -0.048181818 0.063209877 -0.026153846 -0.010150754 -0.01 0.03734104 0.004126984 -0.00688172 -0.026728972 -0.00688172 0.00989899 -0.023269231 -0.000408163 0.025649718 -0.01030303 0.010990991 0.039323671 0.109385475 0.082200957 0.005849057 0.057383178 0.04173913 0.029389671 0.036736402 0.037857143 0.129289617 0.059473684 0.064843049 0.121123596 0.117560976 0.10125 0.044390244 0.048248588 0.013975904 0.007654321 0.025464481
Sample Range:
(leave blank to include all observations)
From:
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) 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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