Autocorrelation Function
| 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 | 8.4853 | 0 |
| 1 | -0.36198 | -3.0715 | 0.998498 |
| 2 | 0.046962 | 0.3985 | 0.345727 |
| 3 | -0.011467 | -0.0973 | 0.53862 |
| 4 | -0.136506 | -1.1583 | 0.874714 |
| 5 | -0.145063 | -1.2309 | 0.888817 |
| 6 | -0.003939 | -0.0334 | 0.513287 |
| 7 | -0.003878 | -0.0329 | 0.513079 |
| 8 | 0.075335 | 0.6392 | 0.262348 |
| 9 | 0.07358 | 0.6243 | 0.267187 |
| 10 | 0.008272 | 0.0702 | 0.472119 |
| 11 | 0.011396 | 0.0967 | 0.461618 |
| 12 | 0.019534 | 0.1657 | 0.43441 |
| 13 | -0.07223 | -0.6129 | 0.729061 |
| 14 | -0.007286 | -0.0618 | 0.524564 |
| 15 | -0.03969 | -0.3368 | 0.63137 |
| 16 | 0.001842 | 0.0156 | 0.493787 |
| 17 | 0.079509 | 0.6747 | 0.251028 |
| 18 | -0.043755 | -0.3713 | 0.644236 |
| 19 | -0.046867 | -0.3977 | 0.653979 |
| 20 | 0.097947 | 0.8311 | 0.20433 |
| 21 | 0.04375 | 0.3712 | 0.355777 |
| 22 | -0.025888 | -0.2197 | 0.586623 |
| 23 | -0.032032 | -0.2718 | 0.606723 |
| 24 | -0.063931 | -0.5425 | 0.705415 |
| 25 | -0.023915 | -0.2029 | 0.580118 |
| 26 | -0.047486 | -0.4029 | 0.655905 |
| 27 | 0.026154 | 0.2219 | 0.412501 |
| 28 | 0.124185 | 1.0537 | 0.147761 |
| 29 | 0.058631 | 0.4975 | 0.310177 |
| 30 | -0.037403 | -0.3174 | 0.624063 |
| 31 | 0.018492 | 0.1569 | 0.437879 |
| 32 | -0.007666 | -0.065 | 0.525842 |
| 33 | -0.081716 | -0.6934 | 0.754849 |
| 34 | -0.014096 | -0.1196 | 0.547436 |
| 35 | -0.01892 | -0.1605 | 0.563547 |
| 36 | -0.01974 | -0.1675 | 0.566276 |
| 37 | 0.046193 | 0.392 | 0.348123 |
| 38 | 0.000218 | 0.0019 | 0.499264 |
| 39 | 0.025635 | 0.2175 | 0.414208 |
| 40 | -0.005549 | -0.0471 | 0.518713 |
| 41 | -0.008521 | -0.0723 | 0.528718 |
| 42 | -0.00648 | -0.055 | 0.521847 |
| 43 | 0.001687 | 0.0143 | 0.494308 |
| 44 | 0.007951 | 0.0675 | 0.473197 |
| 45 | 0.01203 | 0.1021 | 0.459489 |
| 46 | -0.003762 | -0.0319 | 0.512688 |
| 47 | -0.009953 | -0.0845 | 0.533535 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.36198 | -3.0715 | 0.998498 |
| 1 | -0.096744 | -0.8209 | 0.792794 |
| 2 | -0.032343 | -0.2744 | 0.607735 |
| 3 | -0.171705 | -1.457 | 0.925264 |
| 4 | -0.31072 | -2.6366 | 0.994874 |
| 5 | -0.255236 | -2.1657 | 0.983178 |
| 6 | -0.199369 | -1.6917 | 0.952487 |
| 7 | -0.111226 | -0.9438 | 0.825781 |
| 8 | -0.065993 | -0.56 | 0.711382 |
| 9 | -0.112102 | -0.9512 | 0.827662 |
| 10 | -0.122417 | -1.0387 | 0.848799 |
| 11 | -0.049561 | -0.4205 | 0.662328 |
| 12 | -0.068369 | -0.5801 | 0.71818 |
| 13 | -0.052584 | -0.4462 | 0.671602 |
| 14 | -0.091704 | -0.7781 | 0.78048 |
| 15 | -0.089424 | -0.7588 | 0.774773 |
| 16 | 0.027103 | 0.23 | 0.40938 |
| 17 | -0.033426 | -0.2836 | 0.611246 |
| 18 | -0.165725 | -1.4062 | 0.91802 |
| 19 | -0.063523 | -0.539 | 0.70423 |
| 20 | 0.098616 | 0.8368 | 0.20274 |
| 21 | 0.115972 | 0.9841 | 0.164192 |
| 22 | 0.007479 | 0.0635 | 0.474786 |
| 23 | -0.113363 | -0.9619 | 0.830345 |
| 24 | -0.088799 | -0.7535 | 0.773192 |
| 25 | -0.087363 | -0.7413 | 0.769537 |
| 26 | -0.070213 | -0.5958 | 0.723404 |
| 27 | 0.032507 | 0.2758 | 0.391734 |
| 28 | 0.065846 | 0.5587 | 0.289043 |
| 29 | -0.027142 | -0.2303 | 0.590747 |
| 30 | -0.019948 | -0.1693 | 0.566969 |
| 31 | 0.077546 | 0.658 | 0.25632 |
| 32 | 0.083053 | 0.7047 | 0.241627 |
| 33 | 0.086086 | 0.7305 | 0.233738 |
| 34 | 0.087402 | 0.7416 | 0.230362 |
| 35 | 0.046589 | 0.3953 | 0.346887 |
| 36 | 0.014518 | 0.1232 | 0.451151 |
| 37 | -0.034434 | -0.2922 | 0.614505 |
| 38 | 0.006535 | 0.0555 | 0.477965 |
| 39 | -0.000349 | -0.003 | 0.501177 |
| 40 | -0.051268 | -0.435 | 0.667578 |
| 41 | -0.095913 | -0.8138 | 0.790792 |
| 42 | -0.097145 | -0.8243 | 0.793754 |
| 43 | -0.06767 | -0.5742 | 0.716189 |
| 44 | -0.052334 | -0.4441 | 0.670837 |
| 45 | -0.029653 | -0.2516 | 0.598972 |
| 46 | -0.004425 | -0.0375 | 0.514924 |
| 47 | -0.047058 | -0.3993 | 0.654574 |
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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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Software written by Ed van Stee & Patrick Wessa
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