Opdracht 3 Q2 Kolom3
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 1 seconds |
| R Server | 'Gwilym Jenkins' @ 72.249.127.135 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 7.746 | 0 |
| 1 | 0.317678 | 2.4607 | 0.00838 |
| 2 | 0.105717 | 0.8189 | 0.208047 |
| 3 | 0.105576 | 0.8178 | 0.208356 |
| 4 | 0.058769 | 0.4552 | 0.325296 |
| 5 | 0.068531 | 0.5308 | 0.298745 |
| 6 | -0.017274 | -0.1338 | 0.552997 |
| 7 | -0.162077 | -1.2554 | 0.892907 |
| 8 | -0.093528 | -0.7245 | 0.764203 |
| 9 | -0.151304 | -1.172 | 0.877084 |
| 10 | -0.065178 | -0.5049 | 0.692249 |
| 11 | -0.122295 | -0.9473 | 0.826356 |
| 12 | -0.339156 | -2.6271 | 0.994542 |
| 13 | -0.10309 | -0.7985 | 0.786144 |
| 14 | -0.015221 | -0.1179 | 0.54673 |
| 15 | -0.084731 | -0.6563 | 0.742937 |
| 16 | -0.167344 | -1.2962 | 0.900072 |
| 17 | -0.029765 | -0.2306 | 0.590779 |
| 18 | 0.015027 | 0.1164 | 0.453863 |
| 19 | 0.06755 | 0.5232 | 0.301368 |
| 20 | -0.079602 | -0.6166 | 0.730082 |
| 21 | 0.035942 | 0.2784 | 0.39083 |
| 22 | -0.003626 | -0.0281 | 0.511157 |
| 23 | 0.003394 | 0.0263 | 0.489557 |
| 24 | 0.088201 | 0.6832 | 0.248555 |
| 25 | 0.098951 | 0.7665 | 0.223201 |
| 26 | 0.061988 | 0.4802 | 0.316432 |
| 27 | 0.14231 | 1.1023 | 0.13736 |
| 28 | 0.116271 | 0.9006 | 0.185693 |
| 29 | -0.000365 | -0.0028 | 0.501122 |
| 30 | -0.003814 | -0.0295 | 0.511736 |
| 31 | -0.033409 | -0.2588 | 0.601656 |
| 32 | 0.074696 | 0.5786 | 0.282515 |
| 33 | -0.126461 | -0.9796 | 0.834382 |
| 34 | -0.166038 | -1.2861 | 0.898329 |
| 35 | -0.046197 | -0.3578 | 0.63914 |
| 36 | -0.082873 | -0.6419 | 0.738319 |
| 37 | -0.021364 | -0.1655 | 0.565441 |
| 38 | -0.000727 | -0.0056 | 0.502236 |
| 39 | -0.001544 | -0.012 | 0.504753 |
| 40 | 0.099535 | 0.771 | 0.221867 |
| 41 | 0.025788 | 0.1998 | 0.421174 |
| 42 | 0.004803 | 0.0372 | 0.485224 |
| 43 | -0.01531 | -0.1186 | 0.547001 |
| 44 | -0.071303 | -0.5523 | 0.708606 |
| 45 | 0.087483 | 0.6776 | 0.250302 |
| 46 | 0.089753 | 0.6952 | 0.244799 |
| 47 | -0.033298 | -0.2579 | 0.601326 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.317678 | 2.4607 | 0.00838 |
| 1 | 0.005336 | 0.0413 | 0.483583 |
| 2 | 0.078389 | 0.6072 | 0.273005 |
| 3 | 0.002915 | 0.0226 | 0.49103 |
| 4 | 0.048044 | 0.3722 | 0.355546 |
| 5 | -0.06704 | -0.5193 | 0.697266 |
| 6 | -0.162729 | -1.2605 | 0.893814 |
| 7 | -0.003546 | -0.0275 | 0.510912 |
| 8 | -0.124155 | -0.9617 | 0.82997 |
| 9 | 0.047049 | 0.3644 | 0.358406 |
| 10 | -0.1066 | -0.8257 | 0.793882 |
| 11 | -0.275876 | -2.1369 | 0.981655 |
| 12 | 0.104248 | 0.8075 | 0.211284 |
| 13 | 0.000897 | 0.0069 | 0.497241 |
| 14 | -0.069814 | -0.5408 | 0.704667 |
| 15 | -0.18385 | -1.4241 | 0.9202 |
| 16 | 0.117204 | 0.9079 | 0.183792 |
| 17 | -0.032834 | -0.2543 | 0.599946 |
| 18 | -0.017296 | -0.134 | 0.553065 |
| 19 | -0.16808 | -1.3019 | 0.901044 |
| 20 | 0.071353 | 0.5527 | 0.291262 |
| 21 | -0.053459 | -0.4141 | 0.659858 |
| 22 | -0.078756 | -0.61 | 0.727931 |
| 23 | -0.013474 | -0.1044 | 0.541388 |
| 24 | 0.085776 | 0.6644 | 0.254484 |
| 25 | 0.064983 | 0.5034 | 0.308278 |
| 26 | 0.012368 | 0.0958 | 0.461999 |
| 27 | -0.041879 | -0.3244 | 0.626615 |
| 28 | -0.05711 | -0.4424 | 0.670096 |
| 29 | 0.033384 | 0.2586 | 0.398417 |
| 30 | -0.075835 | -0.5874 | 0.720436 |
| 31 | 0.013531 | 0.1048 | 0.458437 |
| 32 | -0.145915 | -1.1303 | 0.868567 |
| 33 | -0.063045 | -0.4883 | 0.686457 |
| 34 | 0.040773 | 0.3158 | 0.376615 |
| 35 | -0.112393 | -0.8706 | 0.806277 |
| 36 | 0.133492 | 1.034 | 0.152637 |
| 37 | -0.053 | -0.4105 | 0.658563 |
| 38 | 0.151818 | 1.176 | 0.122124 |
| 39 | 0.021024 | 0.1629 | 0.435591 |
| 40 | -0.052404 | -0.4059 | 0.656876 |
| 41 | -0.053003 | -0.4106 | 0.658571 |
| 42 | -0.070712 | -0.5477 | 0.707045 |
| 43 | 0.002557 | 0.0198 | 0.49213 |
| 44 | -0.025169 | -0.195 | 0.576959 |
| 45 | 0.040614 | 0.3146 | 0.377081 |
| 46 | -0.039743 | -0.3078 | 0.620368 |
| 47 | -0.022361 | -0.1732 | 0.568466 |
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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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