Autocorrelation Function 3 d=1 D=0
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 5 seconds |
| R Server | 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 7.6811 | 0 |
| 1 | 0.337164 | 2.5898 | 0.006039 |
| 2 | -0.071059 | -0.5458 | 0.706373 |
| 3 | -0.220783 | -1.6959 | 0.952409 |
| 4 | -0.101327 | -0.7783 | 0.780252 |
| 5 | 0.112496 | 0.8641 | 0.195517 |
| 6 | 0.38799 | 2.9802 | 0.002089 |
| 7 | 0.082713 | 0.6353 | 0.263835 |
| 8 | -0.218194 | -1.676 | 0.950483 |
| 9 | -0.22224 | -1.7071 | 0.953465 |
| 10 | -0.090968 | -0.6987 | 0.756269 |
| 11 | 0.361606 | 2.7775 | 0.003666 |
| 12 | 0.477986 | 3.6715 | 0.00026 |
| 13 | 0.291356 | 2.238 | 0.014506 |
| 14 | -0.103432 | -0.7945 | 0.784948 |
| 15 | -0.196342 | -1.5081 | 0.931571 |
| 16 | -0.11201 | -0.8604 | 0.803465 |
| 17 | 0.154743 | 1.1886 | 0.11968 |
| 18 | 0.14584 | 1.1202 | 0.13358 |
| 19 | -0.03642 | -0.2797 | 0.609674 |
| 20 | -0.151991 | -1.1675 | 0.87614 |
| 21 | -0.214471 | -1.6474 | 0.947602 |
| 22 | -0.073163 | -0.562 | 0.711869 |
| 23 | 0.137909 | 1.0593 | 0.146891 |
| 24 | 0.267239 | 2.0527 | 0.022273 |
| 25 | -0.013273 | -0.102 | 0.540429 |
| 26 | -0.132082 | -1.0145 | 0.842766 |
| 27 | -0.160084 | -1.2296 | 0.888142 |
| 28 | -0.005503 | -0.0423 | 0.516788 |
| 29 | 0.035772 | 0.2748 | 0.392226 |
| 30 | 0.028488 | 0.2188 | 0.413772 |
| 31 | -0.09032 | -0.6938 | 0.754724 |
| 32 | -0.174814 | -1.3428 | 0.907755 |
| 33 | -0.110715 | -0.8504 | 0.800736 |
| 34 | -0.024118 | -0.1853 | 0.573167 |
| 35 | 0.045646 | 0.3506 | 0.363564 |
| 36 | -0.032535 | -0.2499 | 0.598235 |
| 37 | -0.031564 | -0.2424 | 0.595362 |
| 38 | -0.138718 | -1.0655 | 0.854508 |
| 39 | -0.100032 | -0.7684 | 0.777332 |
| 40 | -0.011007 | -0.0845 | 0.533545 |
| 41 | 0.018776 | 0.1442 | 0.442908 |
| 42 | -0.057948 | -0.4451 | 0.671063 |
| 43 | -0.06426 | -0.4936 | 0.688287 |
| 44 | -0.095986 | -0.7373 | 0.768063 |
| 45 | -0.074943 | -0.5757 | 0.71648 |
| 46 | 0.001619 | 0.0124 | 0.495061 |
| 47 | -0.023309 | -0.179 | 0.570739 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.337164 | 2.5898 | 0.006039 |
| 1 | -0.208433 | -1.601 | 0.942641 |
| 2 | -0.143375 | -1.1013 | 0.862377 |
| 3 | 0.023738 | 0.1823 | 0.427972 |
| 4 | 0.120414 | 0.9249 | 0.179387 |
| 5 | 0.318579 | 2.4471 | 0.0087 |
| 6 | -0.201499 | -1.5477 | 0.936484 |
| 7 | -0.148451 | -1.1403 | 0.870611 |
| 8 | 0.025881 | 0.1988 | 0.421553 |
| 9 | -0.030697 | -0.2358 | 0.592793 |
| 10 | 0.42709 | 3.2805 | 0.000871 |
| 11 | 0.114292 | 0.8779 | 0.191782 |
| 12 | 0.205344 | 1.5773 | 0.060039 |
| 13 | -0.053251 | -0.409 | 0.657999 |
| 14 | -0.076724 | -0.5893 | 0.721055 |
| 15 | 0.024159 | 0.1856 | 0.426709 |
| 16 | -0.136205 | -1.0462 | 0.850135 |
| 17 | -0.105471 | -0.8101 | 0.789441 |
| 18 | -0.115161 | -0.8846 | 0.81001 |
| 19 | 0.118311 | 0.9088 | 0.183587 |
| 20 | 0.019271 | 0.148 | 0.441414 |
| 21 | -0.105004 | -0.8066 | 0.788418 |
| 22 | -0.064096 | -0.4923 | 0.687845 |
| 23 | -0.030018 | -0.2306 | 0.590779 |
| 24 | -0.213678 | -1.6413 | 0.946972 |
| 25 | -0.076294 | -0.586 | 0.719954 |
| 26 | 0.011228 | 0.0862 | 0.465783 |
| 27 | 0.114438 | 0.879 | 0.19148 |
| 28 | -0.036382 | -0.2795 | 0.609563 |
| 29 | -0.053217 | -0.4088 | 0.657906 |
| 30 | 0.075733 | 0.5817 | 0.281487 |
| 31 | -0.069327 | -0.5325 | 0.701814 |
| 32 | 0.004531 | 0.0348 | 0.486176 |
| 33 | -0.048706 | -0.3741 | 0.64517 |
| 34 | -0.056684 | -0.4354 | 0.66757 |
| 35 | -0.024495 | -0.1881 | 0.574296 |
| 36 | 0.044728 | 0.3436 | 0.366198 |
| 37 | 0.048102 | 0.3695 | 0.356546 |
| 38 | -0.085383 | -0.6558 | 0.742762 |
| 39 | -0.024547 | -0.1885 | 0.574452 |
| 40 | -0.050481 | -0.3878 | 0.650204 |
| 41 | 0.032672 | 0.251 | 0.401359 |
| 42 | 0.034341 | 0.2638 | 0.396435 |
| 43 | -0.117801 | -0.9048 | 0.815387 |
| 44 | 0.041634 | 0.3198 | 0.375125 |
| 45 | -0.012505 | -0.0961 | 0.538098 |
| 46 | 0.000448 | 0.0034 | 0.498632 |
| 47 | -0.070866 | -0.5443 | 0.705868 |
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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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