Workshop 5 Q1 wisselkoers
| 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 | -0.237156 | -1.8216 | 0.963209 |
| 2 | -0.288173 | -2.2135 | 0.984629 |
| 3 | -0.143389 | -1.1014 | 0.8624 |
| 4 | 0.22073 | 1.6955 | 0.04763 |
| 5 | 0.153059 | 1.1757 | 0.122226 |
| 6 | -0.319923 | -2.4574 | 0.991523 |
| 7 | 0.072416 | 0.5562 | 0.290076 |
| 8 | 0.004214 | 0.0324 | 0.487144 |
| 9 | 0.078797 | 0.6052 | 0.273667 |
| 10 | -0.043073 | -0.3308 | 0.629034 |
| 11 | 0.030181 | 0.2318 | 0.408738 |
| 12 | -0.047242 | -0.3629 | 0.641001 |
| 13 | -0.022284 | -0.1712 | 0.567659 |
| 14 | 0.17648 | 1.3556 | 0.090202 |
| 15 | -0.078553 | -0.6034 | 0.725716 |
| 16 | -0.141668 | -1.0882 | 0.859528 |
| 17 | 0.00609 | 0.0468 | 0.481425 |
| 18 | 0.085173 | 0.6542 | 0.257753 |
| 19 | 0.07924 | 0.6087 | 0.272545 |
| 20 | -0.091911 | -0.706 | 0.758511 |
| 21 | -0.01867 | -0.1434 | 0.556771 |
| 22 | 0.035637 | 0.2737 | 0.392624 |
| 23 | 0.047848 | 0.3675 | 0.35727 |
| 24 | 0.032953 | 0.2531 | 0.400529 |
| 25 | -0.139733 | -1.0733 | 0.856249 |
| 26 | -0.02352 | -0.1807 | 0.571375 |
| 27 | 0.090976 | 0.6988 | 0.243712 |
| 28 | 0.068309 | 0.5247 | 0.300883 |
| 29 | -0.064358 | -0.4943 | 0.688551 |
| 30 | -0.123989 | -0.9524 | 0.827604 |
| 31 | 0.199352 | 1.5313 | 0.065526 |
| 32 | -0.043961 | -0.3377 | 0.631596 |
| 33 | -0.146981 | -1.129 | 0.868262 |
| 34 | 0.030501 | 0.2343 | 0.407788 |
| 35 | 0.066573 | 0.5114 | 0.305504 |
| 36 | 0.083521 | 0.6415 | 0.26183 |
| 37 | -0.194783 | -1.4962 | 0.930029 |
| 38 | 0.140933 | 1.0825 | 0.141711 |
| 39 | -0.003716 | -0.0285 | 0.511339 |
| 40 | -0.005829 | -0.0448 | 0.517779 |
| 41 | -0.083206 | -0.6391 | 0.737391 |
| 42 | 0.095128 | 0.7307 | 0.233929 |
| 43 | 0.074048 | 0.5688 | 0.285834 |
| 44 | -0.214464 | -1.6473 | 0.947597 |
| 45 | 0.081813 | 0.6284 | 0.266078 |
| 46 | 0.001174 | 0.009 | 0.496418 |
| 47 | 0.074744 | 0.5741 | 0.284035 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.237156 | -1.8216 | 0.963209 |
| 1 | -0.364941 | -2.8032 | 0.996581 |
| 2 | -0.395102 | -3.0348 | 0.998212 |
| 3 | -0.1189 | -0.9133 | 0.817597 |
| 4 | 0.043415 | 0.3335 | 0.369977 |
| 5 | -0.299171 | -2.298 | 0.987437 |
| 6 | -0.028004 | -0.2151 | 0.584786 |
| 7 | -0.17558 | -1.3487 | 0.908699 |
| 8 | -0.162247 | -1.2462 | 0.8912 |
| 9 | -0.093496 | -0.7182 | 0.762252 |
| 10 | 0.015852 | 0.1218 | 0.45175 |
| 11 | -0.164545 | -1.2639 | 0.894381 |
| 12 | -0.072697 | -0.5584 | 0.710656 |
| 13 | 0.136722 | 1.0502 | 0.148958 |
| 14 | -0.003632 | -0.0279 | 0.51108 |
| 15 | -0.118032 | -0.9066 | 0.815853 |
| 16 | 0.016349 | 0.1256 | 0.450245 |
| 17 | -0.14287 | -1.0974 | 0.861539 |
| 18 | -0.047465 | -0.3646 | 0.641637 |
| 19 | 0.060138 | 0.4619 | 0.322916 |
| 20 | -0.016064 | -0.1234 | 0.548891 |
| 21 | -0.03873 | -0.2975 | 0.61643 |
| 22 | 0.093479 | 0.718 | 0.237787 |
| 23 | 0.106113 | 0.8151 | 0.209155 |
| 24 | -0.077823 | -0.5978 | 0.72386 |
| 25 | -0.017539 | -0.1347 | 0.553355 |
| 26 | 0.065283 | 0.5014 | 0.308962 |
| 27 | -0.030165 | -0.2317 | 0.591216 |
| 28 | 0.060368 | 0.4637 | 0.322287 |
| 29 | 0.023546 | 0.1809 | 0.428548 |
| 30 | 0.154427 | 1.1862 | 0.120154 |
| 31 | -0.008897 | -0.0683 | 0.527128 |
| 32 | -0.160513 | -1.2329 | 0.888752 |
| 33 | -0.038623 | -0.2967 | 0.616118 |
| 34 | -0.118073 | -0.9069 | 0.815934 |
| 35 | -0.056892 | -0.437 | 0.668146 |
| 36 | -0.125037 | -0.9604 | 0.829619 |
| 37 | 0.039146 | 0.3007 | 0.382355 |
| 38 | -0.066258 | -0.5089 | 0.693653 |
| 39 | -0.001033 | -0.0079 | 0.503151 |
| 40 | -0.126396 | -0.9709 | 0.832211 |
| 41 | -0.013309 | -0.1022 | 0.540539 |
| 42 | 0.030072 | 0.231 | 0.409061 |
| 43 | -0.08378 | -0.6435 | 0.738812 |
| 44 | -0.033253 | -0.2554 | 0.600357 |
| 45 | -0.017392 | -0.1336 | 0.552908 |
| 46 | -0.003677 | -0.0282 | 0.511217 |
| 47 | 0.019171 | 0.1473 | 0.441716 |
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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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