partial autocorrelation
| 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 | 7.8102 | 0 |
| 1 | 0.496511 | 3.8779 | 0.00013 |
| 2 | 0.354478 | 2.7686 | 0.003723 |
| 3 | 0.475151 | 3.711 | 0.000224 |
| 4 | 0.510216 | 3.9849 | 9.1e-05 |
| 5 | 0.457028 | 3.5695 | 0.000352 |
| 6 | 0.543718 | 4.2466 | 3.8e-05 |
| 7 | 0.315503 | 2.4642 | 0.008284 |
| 8 | 0.416369 | 3.2519 | 0.000935 |
| 9 | 0.372484 | 2.9092 | 0.002525 |
| 10 | 0.162879 | 1.2721 | 0.104078 |
| 11 | 0.293687 | 2.2938 | 0.012631 |
| 12 | 0.585367 | 4.5719 | 1.2e-05 |
| 13 | 0.189733 | 1.4819 | 0.071762 |
| 14 | 0.120647 | 0.9423 | 0.174881 |
| 15 | 0.142203 | 1.1106 | 0.135542 |
| 16 | 0.128341 | 1.0024 | 0.160061 |
| 17 | 0.149685 | 1.1691 | 0.123461 |
| 18 | 0.159225 | 1.2436 | 0.109205 |
| 19 | -0.033571 | -0.2622 | 0.602973 |
| 20 | 0.070061 | 0.5472 | 0.293121 |
| 21 | 0.015555 | 0.1215 | 0.451851 |
| 22 | -0.174888 | -1.3659 | 0.911511 |
| 23 | -0.004997 | -0.039 | 0.515503 |
| 24 | 0.126205 | 0.9857 | 0.16409 |
| 25 | -0.13833 | -1.0804 | 0.857889 |
| 26 | -0.164456 | -1.2844 | 0.898078 |
| 27 | -0.183135 | -1.4303 | 0.921137 |
| 28 | -0.159957 | -1.2493 | 0.891837 |
| 29 | -0.134516 | -1.0506 | 0.851207 |
| 30 | -0.158007 | -1.2341 | 0.889046 |
| 31 | -0.276812 | -2.162 | 0.982724 |
| 32 | -0.153456 | -1.1985 | 0.882327 |
| 33 | -0.239458 | -1.8702 | 0.966874 |
| 34 | -0.330678 | -2.5827 | 0.993891 |
| 35 | -0.210839 | -1.6467 | 0.947619 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.496511 | 3.8779 | 0.00013 |
| 1 | 0.143275 | 1.119 | 0.133761 |
| 2 | 0.343123 | 2.6799 | 0.004728 |
| 3 | 0.24887 | 1.9437 | 0.028272 |
| 4 | 0.159787 | 1.248 | 0.108404 |
| 5 | 0.303367 | 2.3694 | 0.010499 |
| 6 | -0.219661 | -1.7156 | 0.954345 |
| 7 | 0.202219 | 1.5794 | 0.05971 |
| 8 | -0.202816 | -1.584 | 0.940823 |
| 9 | -0.348236 | -2.7198 | 0.995752 |
| 10 | 0.151145 | 1.1805 | 0.121196 |
| 11 | 0.40023 | 3.1259 | 0.001357 |
| 12 | -0.31201 | -2.4369 | 0.991126 |
| 13 | -0.061736 | -0.4822 | 0.684296 |
| 14 | -0.1691 | -1.3207 | 0.904234 |
| 15 | -0.178613 | -1.395 | 0.915965 |
| 16 | -0.108906 | -0.8506 | 0.800836 |
| 17 | -0.039635 | -0.3096 | 0.621025 |
| 18 | 0.156639 | 1.2234 | 0.112944 |
| 19 | -0.07262 | -0.5672 | 0.713663 |
| 20 | 0.051608 | 0.4031 | 0.344154 |
| 21 | -0.015917 | -0.1243 | 0.549262 |
| 22 | 0.032947 | 0.2573 | 0.398897 |
| 23 | -0.08874 | -0.6931 | 0.754556 |
| 24 | -0.026663 | -0.2082 | 0.582133 |
| 25 | -0.040767 | -0.3184 | 0.624366 |
| 26 | -0.083673 | -0.6535 | 0.742057 |
| 27 | 0.103068 | 0.805 | 0.211978 |
| 28 | -0.173656 | -1.3563 | 0.909998 |
| 29 | 0.068616 | 0.5359 | 0.296985 |
| 30 | -0.024961 | -0.1949 | 0.57696 |
| 31 | 0.009599 | 0.075 | 0.470243 |
| 32 | -0.033779 | -0.2638 | 0.603596 |
| 33 | 0.074471 | 0.5816 | 0.281478 |
| 34 | -0.103261 | -0.8065 | 0.788454 |
| 35 | -0.000739 | -0.0058 | 0.502293 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t11963313810wyyd8gjlwcjejk/2v4ab1196331852.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t11963313810wyyd8gjlwcjejk/2v4ab1196331852.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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