PACF en ACF olie
| 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 | 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 11.3137 | 0 |
| 1 | 0.359607 | 4.0685 | 4.1e-05 |
| 2 | 0.059656 | 0.6749 | 0.250467 |
| 3 | -0.000556 | -0.0063 | 0.502505 |
| 4 | 0.003159 | 0.0357 | 0.485774 |
| 5 | 0.028033 | 0.3172 | 0.375822 |
| 6 | -0.057619 | -0.6519 | 0.742177 |
| 7 | -0.14775 | -1.6716 | 0.951476 |
| 8 | -0.040554 | -0.4588 | 0.676428 |
| 9 | -0.090988 | -1.0294 | 0.847387 |
| 10 | -0.213654 | -2.4172 | 0.991476 |
| 11 | -0.159963 | -1.8098 | 0.963662 |
| 12 | -0.336518 | -3.8073 | 0.999892 |
| 13 | -0.004691 | -0.0531 | 0.521123 |
| 14 | 0.102491 | 1.1595 | 0.124195 |
| 15 | 0.102254 | 1.1569 | 0.124739 |
| 16 | 0.09011 | 1.0195 | 0.154951 |
| 17 | 0.075627 | 0.8556 | 0.196902 |
| 18 | 0.074471 | 0.8425 | 0.200529 |
| 19 | 0.116811 | 1.3216 | 0.094335 |
| 20 | 0.034851 | 0.3943 | 0.347012 |
| 21 | 0.076482 | 0.8653 | 0.194246 |
| 22 | 0.15689 | 1.775 | 0.039136 |
| 23 | -0.016803 | -0.1901 | 0.575235 |
| 24 | -0.213289 | -2.4131 | 0.991383 |
| 25 | -0.229923 | -2.6013 | 0.994809 |
| 26 | -0.004051 | -0.0458 | 0.518243 |
| 27 | 0.002617 | 0.0296 | 0.488213 |
| 28 | -0.10182 | -1.152 | 0.874258 |
| 29 | -0.088263 | -0.9986 | 0.840059 |
| 30 | -0.061268 | -0.6932 | 0.755269 |
| 31 | -0.012942 | -0.1464 | 0.55809 |
| 32 | -0.02741 | -0.3101 | 0.621509 |
| 33 | -0.057686 | -0.6526 | 0.742421 |
| 34 | 0.026851 | 0.3038 | 0.380892 |
| 35 | 0.060698 | 0.6867 | 0.24675 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.359607 | 4.0685 | 4.1e-05 |
| 1 | -0.080007 | -0.9052 | 0.816464 |
| 2 | 0.005832 | 0.066 | 0.473746 |
| 3 | 0.00715 | 0.0809 | 0.467825 |
| 4 | 0.027751 | 0.314 | 0.377028 |
| 5 | -0.090255 | -1.0211 | 0.845437 |
| 6 | -0.10991 | -1.2435 | 0.89202 |
| 7 | 0.063417 | 0.7175 | 0.237192 |
| 8 | -0.119223 | -1.3488 | 0.910117 |
| 9 | -0.176864 | -2.001 | 0.976246 |
| 10 | -0.021306 | -0.2411 | 0.59505 |
| 11 | -0.331764 | -3.7535 | 0.999868 |
| 12 | 0.259314 | 2.9338 | 0.001985 |
| 13 | -0.025686 | -0.2906 | 0.614088 |
| 14 | 0.089283 | 1.0101 | 0.15717 |
| 15 | 0.012837 | 0.1452 | 0.442377 |
| 16 | 0.017091 | 0.1934 | 0.423489 |
| 17 | 0.022276 | 0.252 | 0.400711 |
| 18 | -0.017014 | -0.1925 | 0.576171 |
| 19 | 0.014961 | 0.1693 | 0.432926 |
| 20 | 0.050656 | 0.5731 | 0.28379 |
| 21 | 0.020735 | 0.2346 | 0.40745 |
| 22 | -0.063836 | -0.7222 | 0.764263 |
| 23 | -0.361597 | -4.091 | 0.999962 |
| 24 | 0.136334 | 1.5424 | 0.062718 |
| 25 | 0.14141 | 1.5999 | 0.056046 |
| 26 | -0.04782 | -0.541 | 0.705283 |
| 27 | -0.060453 | -0.6839 | 0.752377 |
| 28 | 0.031869 | 0.3606 | 0.359511 |
| 29 | -0.100268 | -1.1344 | 0.870628 |
| 30 | 0.029913 | 0.3384 | 0.3678 |
| 31 | -0.049426 | -0.5592 | 0.711494 |
| 32 | 0.008567 | 0.0969 | 0.46147 |
| 33 | 0.003512 | 0.0397 | 0.484185 |
| 34 | -0.079248 | -0.8966 | 0.81419 |
| 35 | -0.186178 | -2.1064 | 0.981437 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/30/t1196424523u16st5spcgslbmi/24uxz1196424991.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/30/t1196424523u16st5spcgslbmi/24uxz1196424991.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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