paper tijdreeks 3 autocorr 2
| 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 | 7.6811 | 0 |
| 1 | 0.36347 | 2.7919 | 0.003526 |
| 2 | -0.080942 | -0.6217 | 0.731743 |
| 3 | -0.183395 | -1.4087 | 0.917911 |
| 4 | 0.043305 | 0.3326 | 0.370296 |
| 5 | 0.059489 | 0.4569 | 0.324696 |
| 6 | -0.128567 | -0.9875 | 0.836295 |
| 7 | -0.047053 | -0.3614 | 0.640463 |
| 8 | 0.051365 | 0.3945 | 0.347301 |
| 9 | 0.158212 | 1.2152 | 0.114556 |
| 10 | 0.154239 | 1.1847 | 0.120437 |
| 11 | 0.108877 | 0.8363 | 0.20318 |
| 12 | -0.00489 | -0.0376 | 0.514918 |
| 13 | -0.028421 | -0.2183 | 0.586026 |
| 14 | -0.042702 | -0.328 | 0.627962 |
| 15 | -0.134244 | -1.0311 | 0.846659 |
| 16 | -0.209128 | -1.6063 | 0.943231 |
| 17 | 0.048072 | 0.3692 | 0.356632 |
| 18 | 0.118399 | 0.9094 | 0.18341 |
| 19 | 0.108572 | 0.834 | 0.203834 |
| 20 | -0.08715 | -0.6694 | 0.747078 |
| 21 | -0.035079 | -0.2694 | 0.605736 |
| 22 | 0.010623 | 0.0816 | 0.467623 |
| 23 | -0.171594 | -1.318 | 0.903707 |
| 24 | -0.17289 | -1.328 | 0.905352 |
| 25 | -0.18118 | -1.3917 | 0.915376 |
| 26 | 0.011045 | 0.0848 | 0.46634 |
| 27 | 0.04191 | 0.3219 | 0.374326 |
| 28 | 0.070133 | 0.5387 | 0.29606 |
| 29 | 0.018112 | 0.1391 | 0.444914 |
| 30 | -0.078014 | -0.5992 | 0.724345 |
| 31 | -0.127934 | -0.9827 | 0.835112 |
| 32 | -0.129577 | -0.9953 | 0.838172 |
| 33 | -0.075528 | -0.5801 | 0.717985 |
| 34 | -0.074487 | -0.5721 | 0.715302 |
| 35 | -0.079151 | -0.608 | 0.727231 |
| 36 | -0.099935 | -0.7676 | 0.777112 |
| 37 | -0.038327 | -0.2944 | 0.615256 |
| 38 | 0.068979 | 0.5298 | 0.299106 |
| 39 | 0.082633 | 0.6347 | 0.264034 |
| 40 | -0.004123 | -0.0317 | 0.51258 |
| 41 | -0.072664 | -0.5581 | 0.710571 |
| 42 | -0.071796 | -0.5515 | 0.708305 |
| 43 | 0.003857 | 0.0296 | 0.488234 |
| 44 | -0.017976 | -0.1381 | 0.554675 |
| 45 | -0.047497 | -0.3648 | 0.641728 |
| 46 | -0.036963 | -0.2839 | 0.611266 |
| 47 | 0.052017 | 0.3996 | 0.345465 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.36347 | 2.7919 | 0.003526 |
| 1 | -0.245484 | -1.8856 | 0.967862 |
| 2 | -0.070534 | -0.5418 | 0.704995 |
| 3 | 0.162043 | 1.2447 | 0.109086 |
| 4 | -0.07972 | -0.6123 | 0.728667 |
| 5 | -0.167084 | -1.2834 | 0.897814 |
| 6 | 0.155197 | 1.1921 | 0.119 |
| 7 | -0.019123 | -0.1469 | 0.558138 |
| 8 | 0.085235 | 0.6547 | 0.257603 |
| 9 | 0.149678 | 1.1497 | 0.127453 |
| 10 | 0.0443 | 0.3403 | 0.367429 |
| 11 | -0.070619 | -0.5424 | 0.70522 |
| 12 | 0.074853 | 0.575 | 0.283752 |
| 13 | -0.063703 | -0.4893 | 0.686781 |
| 14 | -0.168069 | -1.291 | 0.899124 |
| 15 | -0.092744 | -0.7124 | 0.760482 |
| 16 | 0.238699 | 1.8335 | 0.035888 |
| 17 | -0.158837 | -1.22 | 0.886349 |
| 18 | 0.076606 | 0.5884 | 0.279248 |
| 19 | -0.068976 | -0.5298 | 0.700887 |
| 20 | -0.008343 | -0.0641 | 0.52544 |
| 21 | -0.087504 | -0.6721 | 0.747937 |
| 22 | -0.162794 | -1.2504 | 0.891962 |
| 23 | 0.009512 | 0.0731 | 0.471003 |
| 24 | -0.113363 | -0.8708 | 0.806293 |
| 25 | 0.053645 | 0.4121 | 0.340895 |
| 26 | 0.038891 | 0.2987 | 0.383099 |
| 27 | -0.01728 | -0.1327 | 0.552572 |
| 28 | -0.024127 | -0.1853 | 0.573194 |
| 29 | -0.08491 | -0.6522 | 0.7416 |
| 30 | -0.136432 | -1.048 | 0.850532 |
| 31 | -0.050572 | -0.3885 | 0.65046 |
| 32 | 0.067507 | 0.5185 | 0.303013 |
| 33 | -0.042056 | -0.323 | 0.626095 |
| 34 | -0.052163 | -0.4007 | 0.654946 |
| 35 | -0.136384 | -1.0476 | 0.85045 |
| 36 | 0.03164 | 0.243 | 0.404413 |
| 37 | -0.033593 | -0.258 | 0.601359 |
| 38 | -0.059999 | -0.4609 | 0.676704 |
| 39 | 0.045894 | 0.3525 | 0.362854 |
| 40 | -0.041274 | -0.317 | 0.623831 |
| 41 | 0.061996 | 0.4762 | 0.317845 |
| 42 | -0.022767 | -0.1749 | 0.569112 |
| 43 | -0.005631 | -0.0433 | 0.517177 |
| 44 | -0.095844 | -0.7362 | 0.767735 |
| 45 | -0.060952 | -0.4682 | 0.679309 |
| 46 | 0.057221 | 0.4395 | 0.330946 |
| 47 | -0.020475 | -0.1573 | 0.562218 |
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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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