Autocorrelation Function
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 1 seconds |
| R Server | 'Gwilym Jenkins' @ 72.249.127.135 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 8.544 | 0 |
| 1 | 0.327604 | 2.799 | 0.003276 |
| 2 | 0.143526 | 1.2263 | 0.112016 |
| 3 | -0.101203 | -0.8647 | 0.804975 |
| 4 | -0.327629 | -2.7993 | 0.996726 |
| 5 | -0.366684 | -3.133 | 0.998754 |
| 6 | -0.208404 | -1.7806 | 0.960431 |
| 7 | -0.047452 | -0.4054 | 0.656827 |
| 8 | 0.110695 | 0.9458 | 0.17369 |
| 9 | 0.167985 | 1.4353 | 0.077741 |
| 10 | 0.126819 | 1.0835 | 0.141067 |
| 11 | 0.070983 | 0.6065 | 0.273039 |
| 12 | 0.000306 | 0.0026 | 0.498961 |
| 13 | -0.093286 | -0.797 | 0.785993 |
| 14 | -0.090291 | -0.7714 | 0.778535 |
| 15 | -0.07684 | -0.6565 | 0.743223 |
| 16 | -0.005384 | -0.046 | 0.518284 |
| 17 | 0.065881 | 0.5629 | 0.287618 |
| 18 | 0.027411 | 0.2342 | 0.407742 |
| 19 | 0.041711 | 0.3564 | 0.361293 |
| 20 | 0.117138 | 1.0008 | 0.160109 |
| 21 | 0.063303 | 0.5409 | 0.295125 |
| 22 | -0.046904 | -0.4007 | 0.655112 |
| 23 | -0.122427 | -1.046 | 0.850497 |
| 24 | -0.156495 | -1.3371 | 0.907328 |
| 25 | -0.102148 | -0.8728 | 0.807171 |
| 26 | -0.009731 | -0.0831 | 0.533017 |
| 27 | 0.145089 | 1.2396 | 0.109539 |
| 28 | 0.254763 | 2.1767 | 0.016369 |
| 29 | 0.192914 | 1.6483 | 0.051799 |
| 30 | 0.051922 | 0.4436 | 0.329315 |
| 31 | -0.037648 | -0.3217 | 0.625688 |
| 32 | -0.141593 | -1.2098 | 0.884865 |
| 33 | -0.226294 | -1.9335 | 0.971471 |
| 34 | -0.161029 | -1.3758 | 0.91346 |
| 35 | -0.121831 | -1.0409 | 0.849328 |
| 36 | -0.05428 | -0.4638 | 0.677905 |
| 37 | 0.03063 | 0.2617 | 0.397143 |
| 38 | 0.043561 | 0.3722 | 0.355418 |
| 39 | 0.05777 | 0.4936 | 0.311541 |
| 40 | -0.004048 | -0.0346 | 0.513749 |
| 41 | -0.023799 | -0.2033 | 0.580282 |
| 42 | -0.023042 | -0.1969 | 0.577761 |
| 43 | -0.003527 | -0.0301 | 0.51198 |
| 44 | 0.014594 | 0.1247 | 0.450554 |
| 45 | 0.021764 | 0.186 | 0.426499 |
| 46 | 0.009208 | 0.0787 | 0.468755 |
| 47 | -0.008181 | -0.0699 | 0.527766 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.327604 | 2.799 | 0.003276 |
| 1 | 0.040554 | 0.3465 | 0.364984 |
| 2 | -0.179084 | -1.5301 | 0.934842 |
| 3 | -0.290178 | -2.4793 | 0.992263 |
| 4 | -0.200424 | -1.7124 | 0.954468 |
| 5 | -0.002844 | -0.0243 | 0.50966 |
| 6 | 0.028427 | 0.2429 | 0.404388 |
| 7 | 0.025157 | 0.2149 | 0.415205 |
| 8 | -0.029849 | -0.255 | 0.600291 |
| 9 | -0.059635 | -0.5095 | 0.694038 |
| 10 | -0.004196 | -0.0359 | 0.51425 |
| 11 | 0.023026 | 0.1967 | 0.422292 |
| 12 | -0.038162 | -0.3261 | 0.627342 |
| 13 | -0.01467 | -0.1253 | 0.5497 |
| 14 | -0.024078 | -0.2057 | 0.581211 |
| 15 | 0.030775 | 0.2629 | 0.396669 |
| 16 | 0.050501 | 0.4315 | 0.333696 |
| 17 | -0.064482 | -0.5509 | 0.708318 |
| 18 | -0.014871 | -0.1271 | 0.550378 |
| 19 | 0.13763 | 1.1759 | 0.121725 |
| 20 | 0.067573 | 0.5773 | 0.282743 |
| 21 | -0.093485 | -0.7987 | 0.786482 |
| 22 | -0.141019 | -1.2049 | 0.883927 |
| 23 | -0.061192 | -0.5228 | 0.698661 |
| 24 | 0.066452 | 0.5678 | 0.285967 |
| 25 | 0.072686 | 0.621 | 0.268257 |
| 26 | 0.097395 | 0.8321 | 0.204021 |
| 27 | 0.09265 | 0.7916 | 0.215579 |
| 28 | -0.01154 | -0.0986 | 0.539137 |
| 29 | -0.056709 | -0.4845 | 0.685266 |
| 30 | 0.033653 | 0.2875 | 0.387262 |
| 31 | 0.038551 | 0.3294 | 0.371407 |
| 32 | -0.063491 | -0.5425 | 0.705424 |
| 33 | -0.035322 | -0.3018 | 0.618166 |
| 34 | -0.08442 | -0.7213 | 0.763481 |
| 35 | -0.113492 | -0.9697 | 0.832295 |
| 36 | -0.089832 | -0.7675 | 0.777378 |
| 37 | -0.060197 | -0.5143 | 0.695709 |
| 38 | 0.005389 | 0.046 | 0.481702 |
| 39 | -0.096982 | -0.8286 | 0.794987 |
| 40 | -0.097227 | -0.8307 | 0.795577 |
| 41 | -0.042363 | -0.3619 | 0.640782 |
| 42 | 0.016525 | 0.1412 | 0.444053 |
| 43 | 0.017646 | 0.1508 | 0.440289 |
| 44 | -0.019133 | -0.1635 | 0.564701 |
| 45 | -0.029102 | -0.2486 | 0.597833 |
| 46 | -0.045916 | -0.3923 | 0.652013 |
| 47 | -0.072431 | -0.6189 | 0.73103 |
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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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