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Data:
0.021999984 4.142192594 -0.972522981 -0.144204686 -1.781329541 -0.841648551 1.713701772 -0.997001107 -1.992103362 -1.294224594 -0.272982625 -1.892018822 1.235760721 0.563031786 -1.681777069 0.409391642 -1.163771183 0.273844923 0.419261998 0.142069989 -1.616052502 0.69356418 0.368288103 1.277297206 -1.42554929 2.687348328 0.117391693 0.100325687 1.041133291 1.723122897 -1.393957144 0.954507778 1.872948154 -2.215147469 -1.926013968 1.104353558 0.582607051 0.89288225 0.384912275 -2.405751477 -0.145150523 -0.56354464 -1.252593096 -0.323909682 -2.902829867 -1.154904595 0.308168949 -0.189829183 2.175477764 0.777371211 -0.027873566 1.082335914 -1.72111969 1.617255615 -0.611267443 -2.651404008 -3.44540633 -0.668921862 0.817370596 1.258840183
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) 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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0 seconds
R Server
Big Analytics Cloud Computing Center
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