autocorrelation - opdracht 3
| 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 | 9 | 0 |
| 1 | 0.087904 | 0.7911 | 0.215587 |
| 2 | -0.218261 | -1.9644 | 0.973541 |
| 3 | 0.034249 | 0.3082 | 0.379346 |
| 4 | -0.099456 | -0.8951 | 0.813307 |
| 5 | 0.25801 | 2.3221 | 0.01137 |
| 6 | 0.416257 | 3.7463 | 0.000167 |
| 7 | 0.193988 | 1.7459 | 0.04231 |
| 8 | -0.078341 | -0.7051 | 0.758605 |
| 9 | -0.065536 | -0.5898 | 0.721524 |
| 10 | -0.253035 | -2.2773 | 0.987298 |
| 11 | 0.09181 | 0.8263 | 0.205534 |
| 12 | 0.720737 | 6.4866 | 0 |
| 13 | 0.000182 | 0.0016 | 0.49935 |
| 14 | -0.238651 | -2.1479 | 0.982643 |
| 15 | -0.039473 | -0.3553 | 0.638339 |
| 16 | -0.147397 | -1.3266 | 0.905811 |
| 17 | 0.153362 | 1.3803 | 0.085653 |
| 18 | 0.291335 | 2.622 | 0.00522 |
| 19 | 0.091893 | 0.827 | 0.205324 |
| 20 | -0.094449 | -0.85 | 0.801095 |
| 21 | -0.091361 | -0.8223 | 0.793326 |
| 22 | -0.272515 | -2.4526 | 0.991835 |
| 23 | 0.060166 | 0.5415 | 0.294827 |
| 24 | 0.520014 | 4.6801 | 6e-06 |
| 25 | -0.041456 | -0.3731 | 0.644979 |
| 26 | -0.187588 | -1.6883 | 0.952399 |
| 27 | -0.072145 | -0.6493 | 0.74101 |
| 28 | -0.163518 | -1.4717 | 0.927506 |
| 29 | 0.103169 | 0.9285 | 0.177949 |
| 30 | 0.183083 | 1.6477 | 0.051639 |
| 31 | 0.081017 | 0.7292 | 0.234005 |
| 32 | -0.059389 | -0.5345 | 0.702771 |
| 33 | -0.12955 | -1.1659 | 0.876472 |
| 34 | -0.232442 | -2.092 | 0.980214 |
| 35 | 0.009389 | 0.0845 | 0.466432 |
| 36 | 0.381316 | 3.4318 | 0.000473 |
| 37 | -0.043076 | -0.3877 | 0.650366 |
| 38 | -0.179926 | -1.6193 | 0.945368 |
| 39 | -0.074792 | -0.6731 | 0.748608 |
| 40 | -0.177205 | -1.5948 | 0.942679 |
| 41 | 0.038381 | 0.3454 | 0.365334 |
| 42 | 0.108776 | 0.979 | 0.165252 |
| 43 | 0.039748 | 0.3577 | 0.360736 |
| 44 | -0.052277 | -0.4705 | 0.680367 |
| 45 | -0.151059 | -1.3595 | 0.911124 |
| 46 | -0.194748 | -1.7527 | 0.958284 |
| 47 | -0.013169 | -0.1185 | 0.547025 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.087904 | 0.7911 | 0.215587 |
| 1 | -0.227748 | -2.0497 | 0.978187 |
| 2 | 0.082721 | 0.7445 | 0.229368 |
| 3 | -0.174156 | -1.5674 | 0.939541 |
| 4 | 0.352914 | 3.1762 | 0.001056 |
| 5 | 0.309895 | 2.7891 | 0.003294 |
| 6 | 0.380515 | 3.4246 | 0.000484 |
| 7 | 0.03503 | 0.3153 | 0.376683 |
| 8 | 0.134281 | 1.2085 | 0.11518 |
| 9 | -0.526269 | -4.7364 | 0.999995 |
| 10 | -0.108405 | -0.9756 | 0.833928 |
| 11 | 0.439001 | 3.951 | 8.3e-05 |
| 12 | -0.064202 | -0.5778 | 0.717504 |
| 13 | -0.047572 | -0.4281 | 0.665159 |
| 14 | -0.033478 | -0.3013 | 0.618021 |
| 15 | 0.081122 | 0.7301 | 0.233718 |
| 16 | -0.127765 | -1.1499 | 0.873213 |
| 17 | -0.093857 | -0.8447 | 0.799621 |
| 18 | -0.078473 | -0.7063 | 0.758974 |
| 19 | 0.022324 | 0.2009 | 0.420634 |
| 20 | 0.13242 | 1.1918 | 0.118414 |
| 21 | 0.002585 | 0.0233 | 0.490747 |
| 22 | -0.001453 | -0.0131 | 0.505202 |
| 23 | -0.027874 | -0.2509 | 0.598722 |
| 24 | 0.039388 | 0.3545 | 0.361947 |
| 25 | 0.015955 | 0.1436 | 0.443089 |
| 26 | -0.061117 | -0.5501 | 0.708103 |
| 27 | -0.049565 | -0.4461 | 0.671636 |
| 28 | -0.003046 | -0.0274 | 0.510901 |
| 29 | -0.069799 | -0.6282 | 0.734177 |
| 30 | 0.097199 | 0.8748 | 0.192136 |
| 31 | 0.000717 | 0.0065 | 0.497434 |
| 32 | -0.024016 | -0.2161 | 0.58529 |
| 33 | 0.035722 | 0.3215 | 0.374331 |
| 34 | -0.07466 | -0.6719 | 0.748233 |
| 35 | -0.002336 | -0.021 | 0.508361 |
| 36 | -0.106099 | -0.9549 | 0.828764 |
| 37 | -0.078655 | -0.7079 | 0.759477 |
| 38 | -0.025841 | -0.2326 | 0.591658 |
| 39 | 0.010578 | 0.0952 | 0.462195 |
| 40 | 0.011954 | 0.1076 | 0.457295 |
| 41 | -0.003404 | -0.0306 | 0.512183 |
| 42 | -0.012659 | -0.1139 | 0.545212 |
| 43 | -0.001051 | -0.0095 | 0.503761 |
| 44 | 0.003261 | 0.0293 | 0.488331 |
| 45 | 0.049112 | 0.442 | 0.329831 |
| 46 | -0.01224 | -0.1102 | 0.543721 |
| 47 | -0.050982 | -0.4588 | 0.67621 |
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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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