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 | 0 |
| 1 | 0.100801 | 0.7056 | 0.241887 |
| 2 | 0.273076 | 1.9115 | 0.030897 |
| 3 | 0.472412 | 3.3069 | 0.000886 |
| 4 | 0.189004 | 1.323 | 0.095983 |
| 5 | 0.259485 | 1.8164 | 0.037715 |
| 6 | 0.246982 | 1.7289 | 0.045064 |
| 7 | -0.137754 | -0.9643 | 0.830179 |
| 8 | 0.146311 | 1.0242 | 0.15539 |
| 9 | 0.042562 | 0.2979 | 0.383507 |
| 10 | -0.211872 | -1.4831 | 0.927775 |
| 11 | -0.129899 | -0.9093 | 0.816178 |
| 12 | -0.169947 | -1.1896 | 0.880038 |
| 13 | -0.238429 | -1.669 | 0.949252 |
| 14 | -0.070071 | -0.4905 | 0.687013 |
| 15 | -0.28042 | -1.9629 | 0.972328 |
| 16 | -0.33148 | -2.3204 | 0.987736 |
| 17 | -0.059531 | -0.4167 | 0.660647 |
| 18 | -0.129527 | -0.9067 | 0.815496 |
| 19 | -0.217639 | -1.5235 | 0.932966 |
| 20 | -0.136809 | -0.9577 | 0.828533 |
| 21 | 0.015015 | 0.1051 | 0.458361 |
| 22 | -0.199052 | -1.3934 | 0.915101 |
| 23 | 0.14382 | 1.0067 | 0.159502 |
| 24 | -0.088284 | -0.618 | 0.730277 |
| 25 | -0.124036 | -0.8683 | 0.805255 |
| 26 | 0.16319 | 1.1423 | 0.129434 |
| 27 | -0.007752 | -0.0543 | 0.521528 |
| 28 | -0.063746 | -0.4462 | 0.671298 |
| 29 | 0.110147 | 0.771 | 0.222196 |
| 30 | -0.054983 | -0.3849 | 0.649005 |
| 31 | 0.068548 | 0.4798 | 0.316739 |
| 32 | 0.023818 | 0.1667 | 0.434136 |
| 33 | -0.091612 | -0.6413 | 0.737837 |
| 34 | 0.05578 | 0.3905 | 0.348945 |
| 35 | 0.060903 | 0.4263 | 0.335871 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.100801 | 0.7056 | 0.241887 |
| 1 | 0.265614 | 1.8593 | 0.034497 |
| 2 | 0.462414 | 3.2369 | 0.001085 |
| 3 | 0.141383 | 0.9897 | 0.163597 |
| 4 | 0.063205 | 0.4424 | 0.330062 |
| 5 | -0.022298 | -0.1561 | 0.561697 |
| 6 | -0.463275 | -3.2429 | 0.998934 |
| 7 | -0.232067 | -1.6245 | 0.944654 |
| 8 | -0.06217 | -0.4352 | 0.667332 |
| 9 | -0.069383 | -0.4857 | 0.68532 |
| 10 | -0.127365 | -0.8916 | 0.811505 |
| 11 | -0.065976 | -0.4618 | 0.676877 |
| 12 | 0.018488 | 0.1294 | 0.448779 |
| 13 | 0.215695 | 1.5099 | 0.06875 |
| 14 | 0.158046 | 1.1063 | 0.136995 |
| 15 | -0.116734 | -0.8171 | 0.791098 |
| 16 | -0.083817 | -0.5867 | 0.719958 |
| 17 | 0.049245 | 0.3447 | 0.365892 |
| 18 | -0.008152 | -0.0571 | 0.522636 |
| 19 | -0.184589 | -1.2921 | 0.898812 |
| 20 | 0.147139 | 1.03 | 0.154041 |
| 21 | -0.252706 | -1.7689 | 0.958436 |
| 22 | 0.059991 | 0.4199 | 0.338184 |
| 23 | 0.015631 | 0.1094 | 0.45666 |
| 24 | -0.102573 | -0.718 | 0.76192 |
| 25 | -0.050535 | -0.3537 | 0.637477 |
| 26 | -0.075472 | -0.5283 | 0.700164 |
| 27 | 0.008604 | 0.0602 | 0.476108 |
| 28 | -0.00509 | -0.0356 | 0.514138 |
| 29 | 0.151554 | 1.0609 | 0.146974 |
| 30 | 0.072342 | 0.5064 | 0.307425 |
| 31 | -0.172195 | -1.2054 | 0.883074 |
| 32 | -0.067506 | -0.4725 | 0.68068 |
| 33 | 0.080563 | 0.5639 | 0.287684 |
| 34 | 0.011091 | 0.0776 | 0.469215 |
| 35 | -0.051576 | -0.361 | 0.640186 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/30/t1196427682r5oh4up5pxryxks/2cz9t1196428331.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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