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Data:
0.0963998702089473 3.68776849361799 -2.21255748827435 -7.20539944007456 -7.023891220501 -7.61148340355811 -3.99320973953091 6.89080433018175 4.29343380939718 7.62272567916079 -11.6843627244492 -0.535869903617174 4.04039602192003 2.32019809603990 9.33968250429729 -2.53778924222572 -1.01815086767597 12.8776109208021 -8.42487576488816 2.83410372215247 -0.471503171874632 -4.91856672164707 7.16052036556875 6.998877306551 1.22749287747846 1.66434155208273 -4.36846797387122 -2.09547670954011 4.81586323198283 -4.48888699863318 -8.48643331579231 2.89866303275703 5.27231601243985 -2.56938765772798 2.36292159333768 -6.05726375617971 4.66991235080987 0.262121137580347 5.3112374408186 -7.91592347989297 6.18741413248122 0.747779670353935 -1.40792915135314 4.52258059154915 0.456098235973329 13.4046188187457 4.19387306989446 2.69556495773171 8.39583369915604 4.06972911185789 1.66853211858185 1.26029425179894 -1.31856162906204 3.42176579549080 4.38702403425957 3.14027069254159
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) 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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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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