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Data:
-26.9187469810882 32.8744894103911 55.4109663077635 -411.74021930021 57.6733735622178 -449.467580506773 -373.137340248775 -371.885251594715 647.419901333695 22.1523877542783 120.184756405119 67.8888126135818 -152.178661617549 231.692049866116 145.757896749545 225.957394015465 337.679773111804 659.938432573688 220.144077848045 568.176791094861 348.725689044856 -773.427865318365 498.389708635609 -602.642888336038 -236.529595990579 -3.05556134451611 392.249606941302 -104.550625738118 682.677984746466 -319.622690673243 315.541864199205 -660.840435581555 -420.191538675928 -277.196633131906 214.812780622531 -48.21289276352 -710.90591577231 -581.694767903059 -463.052580808214 23.9970216115152 -281.457845514168 -536.338283959565 35.4711028984987 241.984287236391 380.351842191102 500.008616098707 182.200659428461 -675.434093805208 198.846676299458 -126.639120920316 186.007671234493 601.909320831046 20.3167706478652 -68.1288136643523 259.690822371878 -61.7095803163634 -647.712671395481 -295.901619189643 -605.509356050111 -98.0460135928702 270.083301724519 -442.28962621432 -38.8754823561344 660.951583193727 -57.644136424814 -231.023832843454 -252.085123860666 115.231008221747 748.358138305777 405.447168684859 -849.686780957183 695.69201774521 175.800002059481 244.333598889478 7.89489699683577 74.8741080775703 -21.1310364513379 462.378549020264 -214.580694131543 -464.829612842442 100.794658470219 517.088500752241 -359.030787129304 -227.250991005292 -634.829212237864 163.911850520385 844.727542077345 -309.728276359043 715.917712584614 831.323241200929 575.223430396836 -675.977091365201 964.10508600436 -985.202233407736 -90.6798552462796 -121.024470824749 -166.838259623166 -26.9771633517265 6.13859746646865 171.057950671142 18.1599008909896 -1161.16622651343 17.8684245729267 -34.0938481545102 413.4749101741 -307.711577146674 602.475786873607 540.065610424555
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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Raw Input
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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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