Autocorrelatie functie - opdracht 3 (d=1 ; D=1)
| 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 | 11.7898 | 0 |
| 1 | -0.563766 | -6.6467 | 1 |
| 2 | 0.102155 | 1.2044 | 0.115244 |
| 3 | 0.138533 | 1.6333 | 0.052337 |
| 4 | -0.162957 | -1.9212 | 0.971625 |
| 5 | 0.045636 | 0.538 | 0.295706 |
| 6 | 0.078111 | 0.9209 | 0.179346 |
| 7 | -0.109932 | -1.2961 | 0.901451 |
| 8 | 0.024734 | 0.2916 | 0.38551 |
| 9 | 0.178151 | 2.1004 | 0.018751 |
| 10 | -0.274739 | -3.2391 | 0.99925 |
| 11 | 0.23395 | 2.7582 | 0.003297 |
| 12 | -0.252923 | -2.9819 | 0.998308 |
| 13 | 0.020888 | 0.2463 | 0.40292 |
| 14 | 0.078444 | 0.9248 | 0.178327 |
| 15 | 0.001879 | 0.0222 | 0.49118 |
| 16 | -0.105638 | -1.2454 | 0.892469 |
| 17 | 0.053137 | 0.6265 | 0.266014 |
| 18 | 0.131588 | 1.5514 | 0.061541 |
| 19 | -0.239395 | -2.8224 | 0.997267 |
| 20 | 0.215026 | 2.5351 | 0.006174 |
| 21 | -0.149188 | -1.7589 | 0.959602 |
| 22 | -0.03428 | -0.4042 | 0.656641 |
| 23 | 0.180675 | 2.1301 | 0.017461 |
| 24 | -0.087929 | -1.0367 | 0.849154 |
| 25 | -0.081822 | -0.9647 | 0.831806 |
| 26 | 0.190972 | 2.2515 | 0.012961 |
| 27 | -0.107602 | -1.2686 | 0.89665 |
| 28 | -0.082712 | -0.9752 | 0.834413 |
| 29 | 0.187007 | 2.2048 | 0.014557 |
| 30 | -0.193917 | -2.2862 | 0.988124 |
| 31 | 0.056656 | 0.668 | 0.252633 |
| 32 | 0.073849 | 0.8707 | 0.192718 |
| 33 | -0.025767 | -0.3038 | 0.619127 |
| 34 | -0.046842 | -0.5523 | 0.709172 |
| 35 | 0.08949 | 1.0551 | 0.146612 |
| 36 | -0.161017 | -1.8984 | 0.97014 |
| 37 | 0.125908 | 1.4844 | 0.069979 |
| 38 | -0.006096 | -0.0719 | 0.528596 |
| 39 | -0.162701 | -1.9182 | 0.971433 |
| 40 | 0.229241 | 2.7027 | 0.003868 |
| 41 | -0.033498 | -0.3949 | 0.653254 |
| 42 | -0.164183 | -1.9357 | 0.972532 |
| 43 | 0.194113 | 2.2886 | 0.011806 |
| 44 | -0.081066 | -0.9558 | 0.829573 |
| 45 | -0.147246 | -1.736 | 0.95761 |
| 46 | 0.216175 | 2.5487 | 0.00595 |
| 47 | -0.03958 | -0.4666 | 0.679258 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.563766 | -6.6467 | 1 |
| 1 | -0.316165 | -3.7275 | 0.99986 |
| 2 | 0.058779 | 0.693 | 0.244734 |
| 3 | -0.002874 | -0.0339 | 0.51349 |
| 4 | -0.068269 | -0.8049 | 0.788868 |
| 5 | 0.047283 | 0.5575 | 0.289055 |
| 6 | 4.2e-05 | 5e-04 | 0.499804 |
| 7 | -0.068745 | -0.8105 | 0.790479 |
| 8 | 0.204036 | 2.4055 | 0.008732 |
| 9 | -0.044351 | -0.5229 | 0.699058 |
| 10 | 0.055988 | 0.6601 | 0.255144 |
| 11 | -0.265666 | -3.1322 | 0.998942 |
| 12 | -0.299094 | -3.5263 | 0.999714 |
| 13 | -0.192981 | -2.2752 | 0.987788 |
| 14 | 0.090494 | 1.0669 | 0.143931 |
| 15 | -0.007795 | -0.0919 | 0.536543 |
| 16 | -0.156676 | -1.8472 | 0.966577 |
| 17 | 0.150338 | 1.7725 | 0.039254 |
| 18 | 0.022059 | 0.2601 | 0.397595 |
| 19 | 0.061171 | 0.7212 | 0.236002 |
| 20 | 0.043992 | 0.5187 | 0.302412 |
| 21 | -0.167716 | -1.9773 | 0.975009 |
| 22 | -0.020996 | -0.2475 | 0.597572 |
| 23 | -0.032829 | -0.3871 | 0.650346 |
| 24 | -0.193395 | -2.2801 | 0.987938 |
| 25 | -0.039762 | -0.4688 | 0.680024 |
| 26 | 0.106298 | 1.2532 | 0.106112 |
| 27 | -0.081177 | -0.9571 | 0.829901 |
| 28 | -0.111288 | -1.3121 | 0.90417 |
| 29 | 0.096542 | 1.1382 | 0.128495 |
| 30 | -0.016234 | -0.1914 | 0.575751 |
| 31 | -0.092039 | -1.0851 | 0.860127 |
| 32 | 0.116752 | 1.3765 | 0.085443 |
| 33 | -0.038798 | -0.4574 | 0.675959 |
| 34 | -0.023538 | -0.2775 | 0.609101 |
| 35 | -0.147122 | -1.7345 | 0.957481 |
| 36 | -0.100305 | -1.1826 | 0.880502 |
| 37 | -0.026731 | -0.3152 | 0.623442 |
| 38 | -0.058735 | -0.6925 | 0.755102 |
| 39 | 0.006933 | 0.0817 | 0.467485 |
| 40 | 0.106703 | 1.258 | 0.105248 |
| 41 | -0.023527 | -0.2774 | 0.60905 |
| 42 | -0.011622 | -0.137 | 0.554395 |
| 43 | -0.033827 | -0.3988 | 0.65468 |
| 44 | -0.065963 | -0.7777 | 0.780965 |
| 45 | -0.120708 | -1.4231 | 0.92153 |
| 46 | 0.101653 | 1.1985 | 0.116386 |
| 47 | -0.087901 | -1.0363 | 0.849078 |
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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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