ACF 3
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 3 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 | 8.9443 | 0 |
| 1 | 0.838566 | 7.5004 | 0 |
| 2 | 0.742581 | 6.6418 | 0 |
| 3 | 0.667919 | 5.974 | 0 |
| 4 | 0.608643 | 5.4439 | 0 |
| 5 | 0.596339 | 5.3338 | 0 |
| 6 | 0.562431 | 5.0305 | 1e-06 |
| 7 | 0.494021 | 4.4187 | 1.5e-05 |
| 8 | 0.449413 | 4.0197 | 6.6e-05 |
| 9 | 0.395573 | 3.5381 | 0.000337 |
| 10 | 0.395234 | 3.5351 | 0.000341 |
| 11 | 0.400062 | 3.5783 | 0.000296 |
| 12 | 0.393026 | 3.5153 | 0.000363 |
| 13 | 0.311238 | 2.7838 | 0.003351 |
| 14 | 0.214493 | 1.9185 | 0.029309 |
| 15 | 0.164635 | 1.4725 | 0.072399 |
| 16 | 0.098492 | 0.8809 | 0.190495 |
| 17 | 0.053921 | 0.4823 | 0.315461 |
| 18 | 0.032849 | 0.2938 | 0.38483 |
| 19 | 0.008596 | 0.0769 | 0.469453 |
| 20 | -0.02005 | -0.1793 | 0.570935 |
| 21 | -0.074397 | -0.6654 | 0.746155 |
| 22 | -0.092 | -0.8229 | 0.793487 |
| 23 | -0.095185 | -0.8514 | 0.801446 |
| 24 | -0.08337 | -0.7457 | 0.770979 |
| 25 | -0.110668 | -0.9898 | 0.837384 |
| 26 | -0.11975 | -1.0711 | 0.856323 |
| 27 | -0.130859 | -1.1704 | 0.87735 |
| 28 | -0.13943 | -1.2471 | 0.892 |
| 29 | -0.128552 | -1.1498 | 0.873175 |
| 30 | -0.103017 | -0.9214 | 0.820196 |
| 31 | -0.087587 | -0.7834 | 0.782148 |
| 32 | -0.080744 | -0.7222 | 0.76386 |
| 33 | -0.116084 | -1.0383 | 0.848867 |
| 34 | -0.118553 | -1.0604 | 0.853916 |
| 35 | -0.122569 | -1.0963 | 0.86188 |
| 36 | -0.119005 | -1.0644 | 0.854827 |
| 37 | -0.107859 | -0.9647 | 0.831204 |
| 38 | -0.103071 | -0.9219 | 0.820322 |
| 39 | -0.09077 | -0.8119 | 0.790363 |
| 40 | -0.099696 | -0.8917 | 0.812389 |
| 41 | -0.107315 | -0.9599 | 0.829989 |
| 42 | -0.09738 | -0.871 | 0.806818 |
| 43 | -0.097822 | -0.8749 | 0.80789 |
| 44 | -0.100811 | -0.9017 | 0.815034 |
| 45 | -0.129501 | -1.1583 | 0.874905 |
| 46 | -0.172621 | -1.544 | 0.936729 |
| 47 | -0.177145 | -1.5844 | 0.94148 |
| 48 | -0.184029 | -1.646 | 0.948157 |
| 49 | -0.213114 | -1.9062 | 0.969889 |
| 50 | -0.184546 | -1.6506 | 0.948633 |
| 51 | -0.18728 | -1.6751 | 0.951089 |
| 52 | -0.193027 | -1.7265 | 0.95594 |
| 53 | -0.171337 | -1.5325 | 0.935326 |
| 54 | -0.186181 | -1.6653 | 0.950113 |
| 55 | -0.186421 | -1.6674 | 0.950328 |
| 56 | -0.179161 | -1.6025 | 0.943503 |
| 57 | -0.197483 | -1.7663 | 0.959424 |
| 58 | -0.205837 | -1.8411 | 0.96534 |
| 59 | -0.215719 | -1.9294 | 0.97139 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.838566 | 7.5004 | 0 |
| 1 | 0.132706 | 1.187 | 0.119379 |
| 2 | 0.056828 | 0.5083 | 0.306326 |
| 3 | 0.042687 | 0.3818 | 0.351811 |
| 4 | 0.159053 | 1.4226 | 0.079367 |
| 5 | -0.001744 | -0.0156 | 0.506204 |
| 6 | -0.115914 | -1.0368 | 0.848516 |
| 7 | 0.018209 | 0.1629 | 0.435516 |
| 8 | -0.033978 | -0.3039 | 0.619006 |
| 9 | 0.130719 | 1.1692 | 0.1229 |
| 10 | 0.056593 | 0.5062 | 0.30706 |
| 11 | 0.02936 | 0.2626 | 0.396765 |
| 12 | -0.243017 | -2.1736 | 0.983654 |
| 13 | -0.173209 | -1.5492 | 0.937363 |
| 14 | 0.030875 | 0.2762 | 0.39157 |
| 15 | -0.138742 | -1.2409 | 0.890874 |
| 16 | -0.064354 | -0.5756 | 0.71675 |
| 17 | 0.054458 | 0.4871 | 0.313764 |
| 18 | 0.114646 | 1.0254 | 0.154126 |
| 19 | -0.028216 | -0.2524 | 0.5993 |
| 20 | -0.143835 | -1.2865 | 0.89901 |
| 21 | 0.026001 | 0.2326 | 0.408348 |
| 22 | -0.007335 | -0.0656 | 0.526072 |
| 23 | 0.087098 | 0.779 | 0.219132 |
| 24 | -0.068917 | -0.6164 | 0.730314 |
| 25 | 0.122975 | 1.0999 | 0.137333 |
| 26 | 0.030447 | 0.2723 | 0.393038 |
| 27 | 0.027313 | 0.2443 | 0.403813 |
| 28 | 0.051115 | 0.4572 | 0.324387 |
| 29 | -0.014959 | -0.1338 | 0.553052 |
| 30 | 0.00265 | 0.0237 | 0.490575 |
| 31 | -0.019753 | -0.1767 | 0.569895 |
| 32 | -0.071728 | -0.6416 | 0.738502 |
| 33 | -0.029559 | -0.2644 | 0.603919 |
| 34 | -0.069387 | -0.6206 | 0.731691 |
| 35 | 0.011615 | 0.1039 | 0.458761 |
| 36 | 0.013464 | 0.1204 | 0.452224 |
| 37 | -0.005676 | -0.0508 | 0.520181 |
| 38 | -0.004966 | -0.0444 | 0.517659 |
| 39 | -0.049516 | -0.4429 | 0.670477 |
| 40 | -0.055 | -0.4919 | 0.687945 |
| 41 | -0.063809 | -0.5707 | 0.715107 |
| 42 | -0.023395 | -0.2092 | 0.582607 |
| 43 | -0.009654 | -0.0863 | 0.534297 |
| 44 | -0.022879 | -0.2046 | 0.580812 |
| 45 | -0.097803 | -0.8748 | 0.807843 |
| 46 | 0.077467 | 0.6929 | 0.245194 |
| 47 | 0.024112 | 0.2157 | 0.414898 |
| 48 | -0.178248 | -1.5943 | 0.942594 |
| 49 | 0.120578 | 1.0785 | 0.14203 |
| 50 | 0.013245 | 0.1185 | 0.452999 |
| 51 | 0.011915 | 0.1066 | 0.457697 |
| 52 | 0.089417 | 0.7998 | 0.213105 |
| 53 | -0.083836 | -0.7499 | 0.772228 |
| 54 | 0.016468 | 0.1473 | 0.441636 |
| 55 | -0.010838 | -0.0969 | 0.53849 |
| 56 | 0.01487 | 0.133 | 0.447263 |
| 57 | -0.078623 | -0.7032 | 0.758022 |
| 58 | -0.039481 | -0.3531 | 0.637541 |
| 59 | -0.000865 | -0.0077 | 0.503077 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/25/t11985846394ft6w5pimm7d47b/2e7pk1198585773.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/25/t11985846394ft6w5pimm7d47b/2e7pk1198585773.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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