(P)ACF voor differencingparameters te bepalen
| 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 | 7.8102 | 0 |
| 1 | 0.856474 | 6.6893 | 0 |
| 2 | 0.654816 | 5.1143 | 2e-06 |
| 3 | 0.488876 | 3.8182 | 0.000158 |
| 4 | 0.375132 | 2.9299 | 0.002382 |
| 5 | 0.334616 | 2.6134 | 0.005637 |
| 6 | 0.291784 | 2.2789 | 0.013093 |
| 7 | 0.206777 | 1.615 | 0.055738 |
| 8 | 0.11125 | 0.8689 | 0.194157 |
| 9 | 0.086737 | 0.6774 | 0.250345 |
| 10 | 0.139541 | 1.0898 | 0.140034 |
| 11 | 0.253893 | 1.983 | 0.025939 |
| 12 | 0.328366 | 2.5646 | 0.006403 |
| 13 | 0.235385 | 1.8384 | 0.035436 |
| 14 | 0.087577 | 0.684 | 0.248283 |
| 15 | -0.041887 | -0.3272 | 0.627663 |
| 16 | -0.121053 | -0.9455 | 0.82592 |
| 17 | -0.143508 | -1.1208 | 0.866624 |
| 18 | -0.167394 | -1.3074 | 0.902007 |
| 19 | -0.214593 | -1.676 | 0.950574 |
| 20 | -0.275192 | -2.1493 | 0.982207 |
| 21 | -0.285062 | -2.2264 | 0.985155 |
| 22 | -0.241681 | -1.8876 | 0.96808 |
| 23 | -0.156609 | -1.2232 | 0.887013 |
| 24 | -0.093635 | -0.7313 | 0.766305 |
| 25 | -0.155067 | -1.2111 | 0.884738 |
| 26 | -0.249245 | -1.9467 | 0.971908 |
| 27 | -0.316876 | -2.4749 | 0.991939 |
| 28 | -0.343747 | -2.6847 | 0.995333 |
| 29 | -0.336095 | -2.625 | 0.994532 |
| 30 | -0.330616 | -2.5822 | 0.993883 |
| 31 | -0.34172 | -2.6689 | 0.995132 |
| 32 | -0.361787 | -2.8256 | 0.996815 |
| 33 | -0.3401 | -2.6563 | 0.994966 |
| 34 | -0.282712 | -2.2081 | 0.984495 |
| 35 | -0.186081 | -1.4533 | 0.924373 |
| 36 | -0.102025 | -0.7968 | 0.785683 |
| 37 | -0.108988 | -0.8512 | 0.801012 |
| 38 | -0.148713 | -1.1615 | 0.875016 |
| 39 | -0.171199 | -1.3371 | 0.906924 |
| 40 | -0.168567 | -1.3166 | 0.903543 |
| 41 | -0.146903 | -1.1473 | 0.872141 |
| 42 | -0.123055 | -0.9611 | 0.829849 |
| 43 | -0.119738 | -0.9352 | 0.823309 |
| 44 | -0.125058 | -0.9767 | 0.833721 |
| 45 | -0.100563 | -0.7854 | 0.782378 |
| 46 | -0.053051 | -0.4143 | 0.659962 |
| 47 | 0.029751 | 0.2324 | 0.408518 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.856474 | 6.6893 | 0 |
| 1 | -0.295477 | -2.3077 | 0.98779 |
| 2 | 0.063316 | 0.4945 | 0.31136 |
| 3 | 0.03639 | 0.2842 | 0.388605 |
| 4 | 0.16034 | 1.2523 | 0.107622 |
| 5 | -0.131227 | -1.0249 | 0.845274 |
| 6 | -0.128284 | -1.0019 | 0.839832 |
| 7 | -0.019538 | -0.1526 | 0.560389 |
| 8 | 0.248317 | 1.9394 | 0.02854 |
| 9 | 0.136468 | 1.0659 | 0.145345 |
| 10 | 0.194194 | 1.5167 | 0.067253 |
| 11 | -0.121508 | -0.949 | 0.826818 |
| 12 | -0.473419 | -3.6975 | 0.999766 |
| 13 | -0.031289 | -0.2444 | 0.596119 |
| 14 | -0.011247 | -0.0878 | 0.534854 |
| 15 | 0.005423 | 0.0424 | 0.483178 |
| 16 | -0.064879 | -0.5067 | 0.692911 |
| 17 | -0.025322 | -0.1978 | 0.578059 |
| 18 | 0.105299 | 0.8224 | 0.207023 |
| 19 | 0.008693 | 0.0679 | 0.473046 |
| 20 | -0.015898 | -0.1242 | 0.549203 |
| 21 | -0.163097 | -1.2738 | 0.896222 |
| 22 | -0.093528 | -0.7305 | 0.766052 |
| 23 | -0.00142 | -0.0111 | 0.504405 |
| 24 | -0.168268 | -1.3142 | 0.903153 |
| 25 | 0.041088 | 0.3209 | 0.374689 |
| 26 | 0.054867 | 0.4285 | 0.334889 |
| 27 | 0.022242 | 0.1737 | 0.431331 |
| 28 | -0.067748 | -0.5291 | 0.700682 |
| 29 | -0.048624 | -0.3798 | 0.647281 |
| 30 | -0.01497 | -0.1169 | 0.546347 |
| 31 | -0.029577 | -0.231 | 0.590959 |
| 32 | -0.044981 | -0.3513 | 0.636716 |
| 33 | -0.074959 | -0.5854 | 0.719797 |
| 34 | 0.071793 | 0.5607 | 0.28852 |
| 35 | 0.090529 | 0.7071 | 0.241113 |
| 36 | 0.004562 | 0.0356 | 0.485846 |
| 37 | -0.088927 | -0.6945 | 0.755009 |
| 38 | -0.031901 | -0.2492 | 0.59796 |
| 39 | -0.038 | -0.2968 | 0.616183 |
| 40 | -0.030519 | -0.2384 | 0.593799 |
| 41 | 0.004359 | 0.034 | 0.486478 |
| 42 | -0.050186 | -0.392 | 0.651775 |
| 43 | 0.052168 | 0.4074 | 0.342553 |
| 44 | 0.046921 | 0.3665 | 0.357642 |
| 45 | 0.002586 | 0.0202 | 0.491977 |
| 46 | 0.002859 | 0.0223 | 0.491128 |
| 47 | 0.033967 | 0.2653 | 0.395841 |
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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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