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Data:
1.59637178246389e-05 -0.000528928079830371 -0.000379615335598625 0.00038524930093652 -0.00119668551397731 -0.00135467218692709 0.000629204239684938 -0.00125782493336941 -0.000715822604743877 -0.00145775397311118 0.00090586820257419 0.00081580291364592 0.000311413531980795 -0.00166616600916562 0.000335811392412256 0.000261623629287684 0.000112788631495469 -0.000465906882130304 -0.000402731982307803 -0.000529094285263005 0.0014484448842795 0.000173569797634477 0.000552904228538073 0.000540233381156932 0.000346921157112578 4.18534624111872e-05 0.000121673297196368 0.000152183353954878 0.000825672173592282 -0.000595892572118315 -0.0016596119546966 0.000881541979379421 -4.41549707230917e-05 0.000682300411395417 0.000854926176340672 -2.69238953622488e-05 0.000638044232975447 -0.000725889945687845 0.000425651240142468 0.00122388400385043 0.000372111611587248 -0.000932593775979713 0.00270510236012386 -7.86119270261397e-06 -0.000838903060403654 -0.00145322482097055 -0.000354536131935043 -0.000296075166764825 -0.000872298503414093 -0.000202893391347205 -0.000573032019690722 0.000283735480154173 -0.000962625097356925 -0.00257385715733466 0.000426805793820473 0.000486954349901254 0.000874136216786315 0.000529738734414838 0.000201257333054092 0.000968867197645315 -0.000157999749148343 -0.000391913356849448 0.0013234746686754 0.00157132368881926 0.000930560870053533 0.00139732391835725 0.000208947115718179 -0.00113966366994638 -0.000914229750354053 -0.000736236352959105 -0.000223780890036181 -0.000260017472186879 -0.000501037085654342 0.00102364951971444 -0.000354192095527308 0.000436463070874258 -0.00128264495060518 0.000491537956533721 -0.00058619492218505 -0.000736939522420208 0.00243816619015008 -0.00142180529586032 -0.00172730814501807 -0.00044083993783304 0.000219270293872929 0.000842857048790155 -0.00237840593168783 0.00014596557065336 0.00117948835793293 0.000329910805631347 0.000226648388377267 -0.00225979467020417 0.000328714382267304 -0.00163686721236423 -0.000191963911771234 -0.000411017424866446 0.000189438721984894 -0.00047832067303762 -1.33068681664467e-05 -0.00120487658809949 -0.000117105368110721 -8.66472262888335e-05 0.000499094461743711 0.00110098299004875 0.00190445867852853 -0.000253274519399314 -7.60427443683426e-05 -0.000257702457573011 -0.00135377245040492 -0.000262263188216794 0.000234369470566086 -0.000783049820634563 -0.000334352481417933 -0.000289677370045081 0.000304824512672808 0.000931577483137732 0.000448460660641138 -7.26094160660303e-05 0.000473142309587238 0.000559454250190315 -7.63680598443844e-05 0.0013155970723939 -0.0014088028705035 0.00080851663739419 0.00176584583722224 0.00114804274728237 -0.00137239739903595 -0.00142887150666404 0.000185555789291147 0.00033925084186637 -0.000111514181852716 0.000480812660515161 -0.000283313402830277 0.000531496360231672 -0.000143961813116484 -0.00121208620240699 -0.000973929770486086 -0.000115373815292925 0.0011199351601504 0.000216136666647929 0.000924239251654146 -0.000165416914692014 0.000151034288287409 -0.000305700504023248 -0.000346757256775254 0.00125379190755259 -0.00105801604376631 -6.71545817948968e-05 -0.00236496708859359 -9.75528703918148e-05 0.000570675622210595 0.000212357650356478 -0.00253695562425985 0.00209663613695227 -6.68604989478825e-05 0.000227606989053541 -0.000624544690875265 0.000266585831246069 -0.00130368062730513 -0.000599433785139688 -0.00101040388726545 0.000268183766744966 -0.00106087009948214 0.000237148554211627 0.000843003314494451 -0.00139130766025808 -0.000734060336315938 -0.000348323438856801 0.000252766813746514 0.000478905852301054 -0.000423978250784498 -0.000412298371434793 -0.000718029042657409 -0.000957329534311428 -0.00171363677882115 0.000244167682494328
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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Computing time
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R Server
Big Analytics Cloud Computing Center
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