methode 2 op tijdreeks 4
| 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 | 7.6811 | 0 |
| 1 | 0.070342 | 0.5403 | 0.29551 |
| 2 | -0.219686 | -1.6874 | 0.951601 |
| 3 | -0.04046 | -0.3108 | 0.621469 |
| 4 | 0.015991 | 0.1228 | 0.45133 |
| 5 | 0.095819 | 0.736 | 0.232323 |
| 6 | 0.061601 | 0.4732 | 0.318921 |
| 7 | -0.153039 | -1.1755 | 0.877744 |
| 8 | 0.033886 | 0.2603 | 0.397777 |
| 9 | 0.008074 | 0.062 | 0.475378 |
| 10 | 0.166599 | 1.2797 | 0.102836 |
| 11 | 0.1667 | 1.2805 | 0.102699 |
| 12 | -0.048312 | -0.3711 | 0.644052 |
| 13 | -0.192623 | -1.4796 | 0.927845 |
| 14 | -0.04605 | -0.3537 | 0.637595 |
| 15 | -0.131324 | -1.0087 | 0.841387 |
| 16 | -0.085143 | -0.654 | 0.742173 |
| 17 | 0.009038 | 0.0694 | 0.472445 |
| 18 | 0.104064 | 0.7993 | 0.213651 |
| 19 | 0.01463 | 0.1124 | 0.455453 |
| 20 | -0.106611 | -0.8189 | 0.791929 |
| 21 | -0.082154 | -0.631 | 0.734772 |
| 22 | 0.106105 | 0.815 | 0.209174 |
| 23 | 0.00325 | 0.025 | 0.490084 |
| 24 | -0.129916 | -0.9979 | 0.838799 |
| 25 | -0.059663 | -0.4583 | 0.675782 |
| 26 | -0.102328 | -0.786 | 0.782492 |
| 27 | 0.010329 | 0.0793 | 0.468515 |
| 28 | 0.148476 | 1.1405 | 0.12935 |
| 29 | -0.042507 | -0.3265 | 0.627401 |
| 30 | -0.0595 | -0.457 | 0.675335 |
| 31 | -0.045144 | -0.3468 | 0.634997 |
| 32 | 0.025244 | 0.1939 | 0.42346 |
| 33 | 0.0835 | 0.6414 | 0.26188 |
| 34 | -0.118033 | -0.9066 | 0.815855 |
| 35 | 0.023925 | 0.1838 | 0.427412 |
| 36 | 0.10097 | 0.7756 | 0.220551 |
| 37 | 0.034113 | 0.262 | 0.397108 |
| 38 | -0.046046 | -0.3537 | 0.637582 |
| 39 | -0.029748 | -0.2285 | 0.589975 |
| 40 | -0.042075 | -0.3232 | 0.626152 |
| 41 | 0.114039 | 0.876 | 0.192304 |
| 42 | 0.005196 | 0.0399 | 0.484148 |
| 43 | -0.082284 | -0.632 | 0.735096 |
| 44 | -0.041694 | -0.3203 | 0.625047 |
| 45 | 0.025964 | 0.1994 | 0.421304 |
| 46 | 0.027896 | 0.2143 | 0.415538 |
| 47 | 0.023847 | 0.1832 | 0.427647 |
| 48 | -0.100901 | -0.775 | 0.779292 |
| 49 | -0.019233 | -0.1477 | 0.55847 |
| 50 | 0.012285 | 0.0944 | 0.462571 |
| 51 | 0.033496 | 0.2573 | 0.398925 |
| 52 | 0.007472 | 0.0574 | 0.477214 |
| 53 | -0.01925 | -0.1479 | 0.558521 |
| 54 | -0.012966 | -0.0996 | 0.539498 |
| 55 | 0.023384 | 0.1796 | 0.429034 |
| 56 | -0.002268 | -0.0174 | 0.50692 |
| 57 | 0.004323 | 0.0332 | 0.486811 |
| 58 | -0.0016 | -0.0123 | 0.504883 |
| 59 | NA | NA | NA |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.070342 | 0.5403 | 0.29551 |
| 1 | -0.225751 | -1.734 | 0.955932 |
| 2 | -0.005971 | -0.0459 | 0.518213 |
| 3 | -0.031384 | -0.2411 | 0.594831 |
| 4 | 0.091742 | 0.7047 | 0.241891 |
| 5 | 0.045534 | 0.3498 | 0.363886 |
| 6 | -0.130126 | -0.9995 | 0.839186 |
| 7 | 0.09158 | 0.7034 | 0.242274 |
| 8 | -0.068658 | -0.5274 | 0.700044 |
| 9 | 0.210548 | 1.6173 | 0.055579 |
| 10 | 0.120721 | 0.9273 | 0.178781 |
| 11 | 0.024976 | 0.1918 | 0.424261 |
| 12 | -0.131715 | -1.0117 | 0.842099 |
| 13 | -0.062865 | -0.4829 | 0.684515 |
| 14 | -0.223383 | -1.7158 | 0.954281 |
| 15 | -0.166392 | -1.2781 | 0.896887 |
| 16 | -0.021721 | -0.1668 | 0.565966 |
| 17 | 0.11614 | 0.8921 | 0.187985 |
| 18 | 0.038848 | 0.2984 | 0.383224 |
| 19 | -0.107488 | -0.8256 | 0.79383 |
| 20 | -0.088544 | -0.6801 | 0.750456 |
| 21 | 0.011193 | 0.086 | 0.465889 |
| 22 | 0.00836 | 0.0642 | 0.47451 |
| 23 | -0.029785 | -0.2288 | 0.590086 |
| 24 | 0.096716 | 0.7429 | 0.230247 |
| 25 | -0.088373 | -0.6788 | 0.750042 |
| 26 | -0.004991 | -0.0383 | 0.515224 |
| 27 | -0.025559 | -0.1963 | 0.577485 |
| 28 | -0.132433 | -1.0172 | 0.843404 |
| 29 | -0.031668 | -0.2432 | 0.595671 |
| 30 | -0.028903 | -0.222 | 0.587464 |
| 31 | 0.070053 | 0.5381 | 0.296271 |
| 32 | 0.013957 | 0.1072 | 0.457494 |
| 33 | -0.105128 | -0.8075 | 0.78869 |
| 34 | 0.115242 | 0.8852 | 0.189825 |
| 35 | 0.00563 | 0.0432 | 0.482827 |
| 36 | 0.094941 | 0.7293 | 0.234365 |
| 37 | -0.057364 | -0.4406 | 0.66945 |
| 38 | -0.027627 | -0.2122 | 0.583661 |
| 39 | -0.111118 | -0.8535 | 0.801586 |
| 40 | 0.052743 | 0.4051 | 0.343423 |
| 41 | -0.027824 | -0.2137 | 0.58425 |
| 42 | -0.069007 | -0.5301 | 0.700967 |
| 43 | -0.026085 | -0.2004 | 0.579058 |
| 44 | -0.050415 | -0.3872 | 0.650015 |
| 45 | -0.074156 | -0.5696 | 0.714444 |
| 46 | -0.097126 | -0.746 | 0.770697 |
| 47 | 0.006339 | 0.0487 | 0.480665 |
| 48 | 0.051545 | 0.3959 | 0.346795 |
| 49 | 0.024772 | 0.1903 | 0.424871 |
| 50 | 0.042396 | 0.3256 | 0.372922 |
| 51 | 0.030356 | 0.2332 | 0.408218 |
| 52 | -0.063097 | -0.4847 | 0.685142 |
| 53 | 0.010874 | 0.0835 | 0.466857 |
| 54 | -0.058582 | -0.45 | 0.672812 |
| 55 | 0.051426 | 0.395 | 0.347131 |
| 56 | 0.025469 | 0.1956 | 0.422786 |
| 57 | -0.003832 | -0.0294 | 0.511691 |
| 58 | NA | NA | NA |
| 59 | NA | NA | NA |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/28/t1196244639fhjn81u29iqgcz1/2tvml1196245227.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/28/t1196244639fhjn81u29iqgcz1/2tvml1196245227.ps (open in new window) |
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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