paper (vrm/ACF) - update 21/12
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 2 seconds |
| R Server | 'Gwilym Jenkins' @ 72.249.127.135 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 7.746 | 0 |
| 1 | 0.305388 | 2.3655 | 0.010627 |
| 2 | 0.078952 | 0.6116 | 0.271569 |
| 3 | 0.087751 | 0.6797 | 0.249649 |
| 4 | -0.013297 | -0.103 | 0.540846 |
| 5 | -0.081506 | -0.6313 | 0.734894 |
| 6 | -0.229905 | -1.7808 | 0.959999 |
| 7 | -0.151415 | -1.1729 | 0.877255 |
| 8 | -0.082348 | -0.6379 | 0.737005 |
| 9 | -0.040095 | -0.3106 | 0.6214 |
| 10 | -0.052277 | -0.4049 | 0.656518 |
| 11 | 0.152674 | 1.1826 | 0.120815 |
| 12 | 0.681703 | 5.2805 | 1e-06 |
| 13 | 0.206913 | 1.6027 | 0.057122 |
| 14 | 0.02249 | 0.1742 | 0.431146 |
| 15 | 0.033461 | 0.2592 | 0.39819 |
| 16 | -0.068936 | -0.534 | 0.702335 |
| 17 | -0.110006 | -0.8521 | 0.801228 |
| 18 | -0.229364 | -1.7766 | 0.959652 |
| 19 | -0.170469 | -1.3204 | 0.90415 |
| 20 | -0.101115 | -0.7832 | 0.781714 |
| 21 | -0.105697 | -0.8187 | 0.791908 |
| 22 | -0.099732 | -0.7725 | 0.77858 |
| 23 | 0.077217 | 0.5981 | 0.276005 |
| 24 | 0.457522 | 3.544 | 0.000385 |
| 25 | 0.142237 | 1.1018 | 0.137482 |
| 26 | 0.004072 | 0.0315 | 0.48747 |
| 27 | -0.013188 | -0.1022 | 0.540512 |
| 28 | -0.062289 | -0.4825 | 0.684392 |
| 29 | -0.092915 | -0.7197 | 0.762753 |
| 30 | -0.183469 | -1.4211 | 0.919774 |
| 31 | -0.095593 | -0.7405 | 0.769045 |
| 32 | -0.043684 | -0.3384 | 0.631869 |
| 33 | -0.046015 | -0.3564 | 0.638616 |
| 34 | -0.037161 | -0.2878 | 0.612772 |
| 35 | 0.054877 | 0.4251 | 0.336152 |
| 36 | 0.366837 | 2.8415 | 0.003063 |
| 37 | 0.11523 | 0.8926 | 0.187827 |
| 38 | 0.02272 | 0.176 | 0.430448 |
| 39 | 0.017391 | 0.1347 | 0.446645 |
| 40 | -0.03076 | -0.2383 | 0.593757 |
| 41 | -0.085579 | -0.6629 | 0.74503 |
| 42 | -0.164564 | -1.2747 | 0.896336 |
| 43 | -0.121061 | -0.9377 | 0.823929 |
| 44 | -0.109803 | -0.8505 | 0.800794 |
| 45 | -0.112725 | -0.8732 | 0.806973 |
| 46 | -0.084878 | -0.6575 | 0.743302 |
| 47 | -0.061333 | -0.4751 | 0.681775 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.305388 | 2.3655 | 0.010627 |
| 1 | -0.015781 | -0.1222 | 0.548442 |
| 2 | 0.0751 | 0.5817 | 0.281467 |
| 3 | -0.067086 | -0.5196 | 0.697389 |
| 4 | -0.067679 | -0.5242 | 0.698977 |
| 5 | -0.211427 | -1.6377 | 0.946641 |
| 6 | -0.018504 | -0.1433 | 0.556746 |
| 7 | -0.020665 | -0.1601 | 0.563319 |
| 8 | 0.027586 | 0.2137 | 0.415762 |
| 9 | -0.054655 | -0.4234 | 0.663224 |
| 10 | 0.194226 | 1.5045 | 0.068854 |
| 11 | 0.653169 | 5.0594 | 2e-06 |
| 12 | -0.257294 | -1.993 | 0.974592 |
| 13 | -0.142263 | -1.102 | 0.862561 |
| 14 | -0.134792 | -1.0441 | 0.849685 |
| 15 | -0.096075 | -0.7442 | 0.770167 |
| 16 | -0.043141 | -0.3342 | 0.630291 |
| 17 | 0.062045 | 0.4806 | 0.316275 |
| 18 | 0.05635 | 0.4365 | 0.332025 |
| 19 | 0.014711 | 0.1139 | 0.454829 |
| 20 | -0.046985 | -0.3639 | 0.641412 |
| 21 | -0.003848 | -0.0298 | 0.51184 |
| 22 | -0.035108 | -0.2719 | 0.606702 |
| 23 | -0.070247 | -0.5441 | 0.705817 |
| 24 | -0.021872 | -0.1694 | 0.566981 |
| 25 | 0.007559 | 0.0586 | 0.476751 |
| 26 | -0.068631 | -0.5316 | 0.701522 |
| 27 | 0.076745 | 0.5945 | 0.277219 |
| 28 | 0.014729 | 0.1141 | 0.454773 |
| 29 | 0.017439 | 0.1351 | 0.446499 |
| 30 | 0.081843 | 0.634 | 0.26426 |
| 31 | 0.013587 | 0.1052 | 0.458268 |
| 32 | 0.059566 | 0.4614 | 0.323091 |
| 33 | 0.011174 | 0.0866 | 0.465656 |
| 34 | -0.106743 | -0.8268 | 0.794194 |
| 35 | 0.053867 | 0.4173 | 0.338991 |
| 36 | -0.076372 | -0.5916 | 0.721822 |
| 37 | 0.056272 | 0.4359 | 0.332243 |
| 38 | 0.108513 | 0.8405 | 0.201972 |
| 39 | 0.027841 | 0.2157 | 0.414995 |
| 40 | -0.065281 | -0.5057 | 0.692529 |
| 41 | -0.044841 | -0.3473 | 0.635222 |
| 42 | -0.195764 | -1.5164 | 0.932663 |
| 43 | -0.16134 | -1.2497 | 0.891875 |
| 44 | -0.106717 | -0.8266 | 0.794138 |
| 45 | 0.01217 | 0.0943 | 0.462604 |
| 46 | -0.023693 | -0.1835 | 0.572496 |
| 47 | -0.138456 | -1.0725 | 0.8561 |
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par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
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