acf dollar koers d=0 D=0
| 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 | 9.2195 | 0 |
| 1 | 0.955438 | 8.8087 | 0 |
| 2 | 0.907876 | 8.3702 | 0 |
| 3 | 0.870304 | 8.0238 | 0 |
| 4 | 0.838357 | 7.7293 | 0 |
| 5 | 0.805737 | 7.4285 | 0 |
| 6 | 0.769585 | 7.0952 | 0 |
| 7 | 0.733875 | 6.766 | 0 |
| 8 | 0.697427 | 6.43 | 0 |
| 9 | 0.657487 | 6.0617 | 0 |
| 10 | 0.616376 | 5.6827 | 0 |
| 11 | 0.574349 | 5.2952 | 0 |
| 12 | 0.534821 | 4.9308 | 2e-06 |
| 13 | 0.49791 | 4.5905 | 8e-06 |
| 14 | 0.458329 | 4.2256 | 3e-05 |
| 15 | 0.417536 | 3.8495 | 0.000114 |
| 16 | 0.378114 | 3.486 | 0.000389 |
| 17 | 0.338841 | 3.124 | 0.00122 |
| 18 | 0.29528 | 2.7223 | 0.003932 |
| 19 | 0.254127 | 2.3429 | 0.010734 |
| 20 | 0.216771 | 1.9985 | 0.024428 |
| 21 | 0.185717 | 1.7122 | 0.045251 |
| 22 | 0.156988 | 1.4474 | 0.075737 |
| 23 | 0.130025 | 1.1988 | 0.116974 |
| 24 | 0.106094 | 0.9781 | 0.165392 |
| 25 | 0.080276 | 0.7401 | 0.230637 |
| 26 | 0.05562 | 0.5128 | 0.304713 |
| 27 | 0.032502 | 0.2997 | 0.382585 |
| 28 | 0.016583 | 0.1529 | 0.439423 |
| 29 | -0.002675 | -0.0247 | 0.509809 |
| 30 | -0.030874 | -0.2846 | 0.611694 |
| 31 | -0.060386 | -0.5567 | 0.710414 |
| 32 | -0.083655 | -0.7713 | 0.778655 |
| 33 | -0.101139 | -0.9325 | 0.82313 |
| 34 | -0.121738 | -1.1224 | 0.867566 |
| 35 | -0.149979 | -1.3827 | 0.914817 |
| 36 | -0.174725 | -1.6109 | 0.944543 |
| 37 | -0.189806 | -1.7499 | 0.95813 |
| 38 | -0.200746 | -1.8508 | 0.966163 |
| 39 | -0.206813 | -1.9067 | 0.970033 |
| 40 | -0.211731 | -1.9521 | 0.972889 |
| 41 | -0.214892 | -1.9812 | 0.974599 |
| 42 | -0.219883 | -2.0272 | 0.977114 |
| 43 | -0.228989 | -2.1112 | 0.981153 |
| 44 | -0.242164 | -2.2326 | 0.9859 |
| 45 | -0.256723 | -2.3669 | 0.989894 |
| 46 | -0.270562 | -2.4945 | 0.992725 |
| 47 | -0.285204 | -2.6294 | 0.994925 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.955438 | 8.8087 | 0 |
| 1 | -0.057225 | -0.5276 | 0.70042 |
| 2 | 0.091199 | 0.8408 | 0.201406 |
| 3 | 0.036719 | 0.3385 | 0.367899 |
| 4 | -0.017385 | -0.1603 | 0.563481 |
| 5 | -0.045889 | -0.4231 | 0.663347 |
| 6 | -0.010029 | -0.0925 | 0.536727 |
| 7 | -0.037215 | -0.3431 | 0.633815 |
| 8 | -0.063568 | -0.5861 | 0.720308 |
| 9 | -0.036662 | -0.338 | 0.631905 |
| 10 | -0.044492 | -0.4102 | 0.658653 |
| 11 | -0.004533 | -0.0418 | 0.51662 |
| 12 | -0.000658 | -0.0061 | 0.502412 |
| 13 | -0.051848 | -0.478 | 0.683065 |
| 14 | -0.030224 | -0.2787 | 0.609405 |
| 15 | -0.012985 | -0.1197 | 0.547505 |
| 16 | -0.032889 | -0.3032 | 0.61877 |
| 17 | -0.077937 | -0.7185 | 0.762802 |
| 18 | 0.002562 | 0.0236 | 0.490605 |
| 19 | -0.002478 | -0.0228 | 0.509085 |
| 20 | 0.039283 | 0.3622 | 0.359063 |
| 21 | 0.008728 | 0.0805 | 0.468026 |
| 22 | 0.016406 | 0.1513 | 0.440065 |
| 23 | 0.022751 | 0.2098 | 0.41718 |
| 24 | -0.039062 | -0.3601 | 0.64018 |
| 25 | -0.001626 | -0.015 | 0.505962 |
| 26 | -0.010653 | -0.0982 | 0.539005 |
| 27 | 0.05733 | 0.5286 | 0.299245 |
| 28 | -0.073414 | -0.6768 | 0.749827 |
| 29 | -0.113812 | -1.0493 | 0.851492 |
| 30 | -0.04273 | -0.394 | 0.652698 |
| 31 | 0.016443 | 0.1516 | 0.439933 |
| 32 | 0.018095 | 0.1668 | 0.433951 |
| 33 | -0.057513 | -0.5302 | 0.701337 |
| 34 | -0.09557 | -0.8811 | 0.809629 |
| 35 | 0.002687 | 0.0248 | 0.490146 |
| 36 | 0.059638 | 0.5498 | 0.291937 |
| 37 | 0.018492 | 0.1705 | 0.432514 |
| 38 | 0.069222 | 0.6382 | 0.262531 |
| 39 | 0.018793 | 0.1733 | 0.431429 |
| 40 | 0.010384 | 0.0957 | 0.461977 |
| 41 | -0.025845 | -0.2383 | 0.593882 |
| 42 | -0.044237 | -0.4078 | 0.657793 |
| 43 | -0.064192 | -0.5918 | 0.722231 |
| 44 | -0.069654 | -0.6422 | 0.738756 |
| 45 | -0.043807 | -0.4039 | 0.656343 |
| 46 | -0.052098 | -0.4803 | 0.683883 |
| 47 | 0.01296 | 0.1195 | 0.452586 |
 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196354096z0fuvogrnthr526/1j7bg1196354719.ps (open in new window) |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196354096z0fuvogrnthr526/2rfjk1196354719.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196354096z0fuvogrnthr526/2rfjk1196354719.ps (open in new window) |
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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