| 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 | -0.102261 | -0.8677 | 0.805784 |
| 2 | -0.091381 | -0.7754 | 0.779676 |
| 3 | -0.060962 | -0.5173 | 0.696728 |
| 4 | -0.077001 | -0.6534 | 0.742203 |
| 5 | -0.020646 | -0.1752 | 0.569287 |
| 6 | -0.050697 | -0.4302 | 0.665824 |
| 7 | 0.124894 | 1.0598 | 0.146398 |
| 8 | -0.177453 | -1.5057 | 0.931746 |
| 9 | 0.139043 | 1.1798 | 0.120978 |
| 10 | -0.043133 | -0.366 | 0.642279 |
| 11 | -0.050961 | -0.4324 | 0.666635 |
| 12 | -0.097633 | -0.8284 | 0.794922 |
| 13 | -0.157612 | -1.3374 | 0.907347 |
| 14 | 0.04344 | 0.3686 | 0.356754 |
| 15 | -0.01482 | -0.1258 | 0.54986 |
| 16 | 0.241852 | 2.0522 | 0.021894 |
| 17 | -0.10112 | -0.858 | 0.80314 |
| 18 | -0.108626 | -0.9217 | 0.820124 |
| 19 | -0.027008 | -0.2292 | 0.590309 |
| 20 | 0.048593 | 0.4123 | 0.340663 |
| 21 | 0.019463 | 0.1651 | 0.434646 |
| 22 | -0.053086 | -0.4504 | 0.67313 |
| 23 | 0.205151 | 1.7408 | 0.042998 |
| 24 | -0.15587 | -1.3226 | 0.904923 |
| 25 | 0.015086 | 0.128 | 0.449249 |
| 26 | 0.03562 | 0.3022 | 0.381667 |
| 27 | 0.034116 | 0.2895 | 0.386523 |
| 28 | 0.012797 | 0.1086 | 0.456915 |
| 29 | 0.024844 | 0.2108 | 0.416815 |
| 30 | 0.054173 | 0.4597 | 0.323568 |
| 31 | -0.059261 | -0.5028 | 0.691697 |
| 32 | 0.045316 | 0.3845 | 0.350863 |
| 33 | -0.01055 | -0.0895 | 0.53554 |
| 34 | -0.012131 | -0.1029 | 0.540849 |
| 35 | -0.037102 | -0.3148 | 0.623096 |
| 36 | 0.008449 | 0.0717 | 0.471523 |
| 37 | 0.033373 | 0.2832 | 0.388927 |
| 38 | 0.096435 | 0.8183 | 0.207949 |
| 39 | -0.053588 | -0.4547 | 0.674656 |
| 40 | -0.166915 | -1.4163 | 0.919503 |
| 41 | 0.03601 | 0.3056 | 0.380413 |
| 42 | -0.047221 | -0.4007 | 0.655079 |
| 43 | 0.030361 | 0.2576 | 0.398718 |
| 44 | -0.038996 | -0.3309 | 0.629155 |
| 45 | 0.004514 | 0.0383 | 0.484776 |
| 46 | 0.055682 | 0.4725 | 0.319007 |
| 47 | 0.037909 | 0.3217 | 0.374318 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.102261 | -0.8677 | 0.805784 |
| 1 | -0.102914 | -0.8733 | 0.807287 |
| 2 | -0.083542 | -0.7089 | 0.759655 |
| 3 | -0.106158 | -0.9008 | 0.814645 |
| 4 | -0.060251 | -0.5112 | 0.69463 |
| 5 | -0.090258 | -0.7659 | 0.77687 |
| 6 | 0.086886 | 0.7373 | 0.231681 |
| 7 | -0.191383 | -1.6239 | 0.94562 |
| 8 | 0.111969 | 0.9501 | 0.172623 |
| 9 | -0.066439 | -0.5637 | 0.712662 |
| 10 | -0.045408 | -0.3853 | 0.649424 |
| 11 | -0.148938 | -1.2638 | 0.894807 |
| 12 | -0.20195 | -1.7136 | 0.954548 |
| 13 | -0.090459 | -0.7676 | 0.777374 |
| 14 | -0.071975 | -0.6107 | 0.728349 |
| 15 | 0.120431 | 1.0219 | 0.155127 |
| 16 | -0.09194 | -0.7801 | 0.781065 |
| 17 | -0.170313 | -1.4452 | 0.923624 |
| 18 | -0.106039 | -0.8998 | 0.814379 |
| 19 | -0.002275 | -0.0193 | 0.507673 |
| 20 | -0.07588 | -0.6439 | 0.739145 |
| 21 | -0.080971 | -0.6871 | 0.752873 |
| 22 | 0.08318 | 0.7058 | 0.241294 |
| 23 | -0.15762 | -1.3375 | 0.907358 |
| 24 | -0.127564 | -1.0824 | 0.858661 |
| 25 | -0.073764 | -0.6259 | 0.733322 |
| 26 | 0.014784 | 0.1254 | 0.450259 |
| 27 | 0.016568 | 0.1406 | 0.444297 |
| 28 | 0.052404 | 0.4447 | 0.32895 |
| 29 | -0.054779 | -0.4648 | 0.678266 |
| 30 | -0.035015 | -0.2971 | 0.616381 |
| 31 | -0.091808 | -0.779 | 0.780738 |
| 32 | 0.069471 | 0.5895 | 0.278692 |
| 33 | 0.045555 | 0.3865 | 0.350115 |
| 34 | -0.017298 | -0.1468 | 0.558141 |
| 35 | -0.02231 | -0.1893 | 0.574809 |
| 36 | -0.01146 | -0.0972 | 0.538597 |
| 37 | 0.171765 | 1.4575 | 0.074667 |
| 38 | -0.057386 | -0.4869 | 0.686109 |
| 39 | -0.053186 | -0.4513 | 0.673436 |
| 40 | 0.102332 | 0.8683 | 0.194053 |
| 41 | -0.056856 | -0.4824 | 0.684521 |
| 42 | -0.036838 | -0.3126 | 0.622248 |
| 43 | -0.061703 | -0.5236 | 0.698906 |
| 44 | -0.000359 | -0.003 | 0.501212 |
| 45 | 0.080456 | 0.6827 | 0.248496 |
| 46 | 0.107751 | 0.9143 | 0.181806 |
| 47 | 0.033797 | 0.2868 | 0.387554 |
 |
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 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/01/t1196467448tmlxwp041ishysp/2g2y11196468118.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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