WS 4 - Q2 - methode 2 - Reeks 1 (2)
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 3 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 | 6.9282 | 0 |
| 1 | 0.068634 | 0.4755 | 0.318291 |
| 2 | -0.056275 | -0.3899 | 0.650826 |
| 3 | 0.123806 | 0.8578 | 0.197646 |
| 4 | 0.034238 | 0.2372 | 0.406752 |
| 5 | 0.037682 | 0.2611 | 0.397579 |
| 6 | 0.158482 | 1.098 | 0.138843 |
| 7 | -0.125543 | -0.8698 | 0.805627 |
| 8 | 0.006089 | 0.0422 | 0.483262 |
| 9 | 0.11713 | 0.8115 | 0.210543 |
| 10 | -0.201954 | -1.3992 | 0.915906 |
| 11 | -0.162493 | -1.1258 | 0.867072 |
| 12 | -0.166641 | -1.1545 | 0.872999 |
| 13 | -0.088363 | -0.6122 | 0.728352 |
| 14 | 0.073963 | 0.5124 | 0.305349 |
| 15 | -0.150396 | -1.042 | 0.848678 |
| 16 | -0.170269 | -1.1797 | 0.878024 |
| 17 | 0.153317 | 1.0622 | 0.146728 |
| 18 | -0.054993 | -0.381 | 0.647559 |
| 19 | -0.195946 | -1.3576 | 0.909523 |
| 20 | 0.013966 | 0.0968 | 0.46166 |
| 21 | 0.083004 | 0.5751 | 0.283966 |
| 22 | -0.045735 | -0.3169 | 0.623638 |
| 23 | 0.157351 | 1.0902 | 0.140543 |
| 24 | -0.191592 | -1.3274 | 0.90467 |
| 25 | -0.117204 | -0.812 | 0.789604 |
| 26 | 0.088527 | 0.6133 | 0.271276 |
| 27 | 0.127444 | 0.883 | 0.19083 |
| 28 | -0.041755 | -0.2893 | 0.613196 |
| 29 | 0.078839 | 0.5462 | 0.293726 |
| 30 | 0.010481 | 0.0726 | 0.471208 |
| 31 | 0.075766 | 0.5249 | 0.301028 |
| 32 | 0.007624 | 0.0528 | 0.479046 |
| 33 | -0.169109 | -1.1716 | 0.876434 |
| 34 | 0.06885 | 0.477 | 0.317761 |
| 35 | 0.061445 | 0.4257 | 0.336114 |
| 36 | 0.00264 | 0.0183 | 0.492741 |
| 37 | 0.087826 | 0.6085 | 0.27287 |
| 38 | -0.00704 | -0.0488 | 0.51935 |
| 39 | -0.104383 | -0.7232 | 0.763462 |
| 40 | 0.03559 | 0.2466 | 0.403144 |
| 41 | -0.06199 | -0.4295 | 0.665251 |
| 42 | -0.089843 | -0.6224 | 0.731703 |
| 43 | 0.095351 | 0.6606 | 0.25601 |
| 44 | 0.065078 | 0.4509 | 0.327056 |
| 45 | -0.073128 | -0.5066 | 0.692639 |
| 46 | -0.034774 | -0.2409 | 0.594678 |
| 47 | -0.023698 | -0.1642 | 0.564861 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.068634 | 0.4755 | 0.318291 |
| 1 | -0.061274 | -0.4245 | 0.663458 |
| 2 | 0.133236 | 0.9231 | 0.18029 |
| 3 | 0.011367 | 0.0788 | 0.468778 |
| 4 | 0.051666 | 0.358 | 0.360974 |
| 5 | 0.142271 | 0.9857 | 0.164616 |
| 6 | -0.155195 | -1.0752 | 0.856174 |
| 7 | 0.042265 | 0.2928 | 0.385461 |
| 8 | 0.058933 | 0.4083 | 0.342436 |
| 9 | -0.209325 | -1.4502 | 0.923254 |
| 10 | -0.129944 | -0.9003 | 0.813766 |
| 11 | -0.230271 | -1.5954 | 0.941402 |
| 12 | -0.011266 | -0.0781 | 0.530944 |
| 13 | 0.08523 | 0.5905 | 0.278816 |
| 14 | -0.158868 | -1.1007 | 0.861735 |
| 15 | -0.014668 | -0.1016 | 0.540259 |
| 16 | 0.176038 | 1.2196 | 0.114282 |
| 17 | -0.051488 | -0.3567 | 0.638567 |
| 18 | -0.14976 | -1.0376 | 0.847665 |
| 19 | -0.030744 | -0.213 | 0.583887 |
| 20 | 0.155234 | 1.0755 | 0.143765 |
| 21 | -0.153746 | -1.0652 | 0.85394 |
| 22 | 0.021809 | 0.1511 | 0.440267 |
| 23 | -0.200069 | -1.3861 | 0.913941 |
| 24 | -0.071795 | -0.4974 | 0.689414 |
| 25 | -0.054164 | -0.3753 | 0.64544 |
| 26 | 0.116983 | 0.8105 | 0.210832 |
| 27 | 0.026487 | 0.1835 | 0.427585 |
| 28 | 0.089662 | 0.6212 | 0.268704 |
| 29 | -0.020682 | -0.1433 | 0.55667 |
| 30 | 0.030881 | 0.214 | 0.415746 |
| 31 | -0.048544 | -0.3363 | 0.630953 |
| 32 | -0.12116 | -0.8394 | 0.797303 |
| 33 | -0.031057 | -0.2152 | 0.584728 |
| 34 | -0.095773 | -0.6635 | 0.744918 |
| 35 | 0.006668 | 0.0462 | 0.481673 |
| 36 | 0.053076 | 0.3677 | 0.357348 |
| 37 | -0.002719 | -0.0188 | 0.507476 |
| 38 | 0.030309 | 0.21 | 0.417284 |
| 39 | -0.054865 | -0.3801 | 0.647232 |
| 40 | 0.005702 | 0.0395 | 0.484327 |
| 41 | 0.014678 | 0.1017 | 0.459713 |
| 42 | -0.002955 | -0.0205 | 0.508125 |
| 43 | -0.040741 | -0.2823 | 0.610521 |
| 44 | -0.039753 | -0.2754 | 0.60791 |
| 45 | -0.071077 | -0.4924 | 0.687671 |
| 46 | 0.057521 | 0.3985 | 0.346007 |
| 47 | NA | NA | NA |
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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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