paper diesel (vrm/acf lambda=1)
| 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 | 7.746 | 0 |
| 1 | 0.944417 | 7.3154 | 0 |
| 2 | 0.865982 | 6.7079 | 0 |
| 3 | 0.778547 | 6.0306 | 0 |
| 4 | 0.699128 | 5.4154 | 1e-06 |
| 5 | 0.626811 | 4.8553 | 4e-06 |
| 6 | 0.551329 | 4.2706 | 3.5e-05 |
| 7 | 0.477675 | 3.7001 | 0.000235 |
| 8 | 0.419913 | 3.2526 | 0.00094 |
| 9 | 0.367283 | 2.845 | 0.003034 |
| 10 | 0.332021 | 2.5718 | 0.006306 |
| 11 | 0.29936 | 2.3188 | 0.011914 |
| 12 | 0.25566 | 1.9803 | 0.026128 |
| 13 | 0.200218 | 1.5509 | 0.063095 |
| 14 | 0.137463 | 1.0648 | 0.14562 |
| 15 | 0.070068 | 0.5427 | 0.294659 |
| 16 | 0.018422 | 0.1427 | 0.443504 |
| 17 | -0.021903 | -0.1697 | 0.567075 |
| 18 | -0.053509 | -0.4145 | 0.659998 |
| 19 | -0.085677 | -0.6637 | 0.745272 |
| 20 | -0.127127 | -0.9847 | 0.835642 |
| 21 | -0.161194 | -1.2486 | 0.89167 |
| 22 | -0.181339 | -1.4046 | 0.917358 |
| 23 | -0.192976 | -1.4948 | 0.929894 |
| 24 | -0.197792 | -1.5321 | 0.934622 |
| 25 | -0.206476 | -1.5994 | 0.942503 |
| 26 | -0.218675 | -1.6939 | 0.95226 |
| 27 | -0.219906 | -1.7034 | 0.953164 |
| 28 | -0.218183 | -1.69 | 0.951895 |
| 29 | -0.215898 | -1.6723 | 0.950167 |
| 30 | -0.207214 | -1.6051 | 0.943136 |
| 31 | -0.207109 | -1.6043 | 0.943046 |
| 32 | -0.210027 | -1.6269 | 0.945496 |
| 33 | -0.224336 | -1.7377 | 0.956302 |
| 34 | -0.24666 | -1.9106 | 0.969582 |
| 35 | -0.254641 | -1.9724 | 0.973413 |
| 36 | -0.260231 | -2.0157 | 0.975844 |
| 37 | -0.266032 | -2.0607 | 0.978161 |
| 38 | -0.273028 | -2.1149 | 0.980698 |
| 39 | -0.284594 | -2.2045 | 0.984331 |
| 40 | -0.284067 | -2.2004 | 0.984179 |
| 41 | -0.273344 | -2.1173 | 0.980806 |
| 42 | -0.264731 | -2.0506 | 0.977659 |
| 43 | -0.25682 | -1.9893 | 0.974385 |
| 44 | -0.247926 | -1.9204 | 0.97022 |
| 45 | -0.230804 | -1.7878 | 0.960571 |
| 46 | -0.205245 | -1.5898 | 0.941435 |
| 47 | -0.177999 | -1.3788 | 0.913458 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.944417 | 7.3154 | 0 |
| 1 | -0.240028 | -1.8593 | 0.966051 |
| 2 | -0.087591 | -0.6785 | 0.749961 |
| 3 | 0.054305 | 0.4206 | 0.337759 |
| 4 | -0.007116 | -0.0551 | 0.521887 |
| 5 | -0.109549 | -0.8486 | 0.80025 |
| 6 | -0.013153 | -0.1019 | 0.540406 |
| 7 | 0.117073 | 0.9068 | 0.184058 |
| 8 | -0.06174 | -0.4782 | 0.682891 |
| 9 | 0.098164 | 0.7604 | 0.225003 |
| 10 | -0.03603 | -0.2791 | 0.609431 |
| 11 | -0.156152 | -1.2095 | 0.884401 |
| 12 | -0.107774 | -0.8348 | 0.796432 |
| 13 | -0.0462 | -0.3579 | 0.639148 |
| 14 | -0.089781 | -0.6954 | 0.755268 |
| 15 | 0.100129 | 0.7756 | 0.220517 |
| 16 | 0.06279 | 0.4864 | 0.314238 |
| 17 | -0.02009 | -0.1556 | 0.561571 |
| 18 | -0.07425 | -0.5751 | 0.716326 |
| 19 | -0.131533 | -1.0188 | 0.843817 |
| 20 | 0.013663 | 0.1058 | 0.458035 |
| 21 | 0.039487 | 0.3059 | 0.380382 |
| 22 | 0.020522 | 0.159 | 0.437115 |
| 23 | 0.033653 | 0.2607 | 0.397618 |
| 24 | -0.00367 | -0.0284 | 0.511292 |
| 25 | -0.03836 | -0.2971 | 0.616306 |
| 26 | 0.059354 | 0.4598 | 0.323677 |
| 27 | -0.062151 | -0.4814 | 0.684016 |
| 28 | -0.089131 | -0.6904 | 0.753699 |
| 29 | 0.083042 | 0.6432 | 0.26126 |
| 30 | -0.051711 | -0.4006 | 0.654913 |
| 31 | -0.032717 | -0.2534 | 0.599598 |
| 32 | -0.103528 | -0.8019 | 0.78712 |
| 33 | -0.078368 | -0.607 | 0.726942 |
| 34 | 0.069993 | 0.5422 | 0.294858 |
| 35 | -0.053973 | -0.4181 | 0.661307 |
| 36 | -0.034062 | -0.2638 | 0.603598 |
| 37 | -0.022346 | -0.1731 | 0.568418 |
| 38 | -0.026887 | -0.2083 | 0.582137 |
| 39 | 0.04564 | 0.3535 | 0.362466 |
| 40 | -0.006312 | -0.0489 | 0.519415 |
| 41 | -0.078523 | -0.6082 | 0.727336 |
| 42 | -0.008898 | -0.0689 | 0.527359 |
| 43 | 0.091047 | 0.7052 | 0.241692 |
| 44 | 0.098621 | 0.7639 | 0.223955 |
| 45 | -0.013176 | -0.1021 | 0.540475 |
| 46 | 0.012055 | 0.0934 | 0.462957 |
| 47 | -0.03703 | -0.2868 | 0.612385 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/13/t1197578390prdjlx0yquvpgdc/176qc1197579284.png (open in new window) |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/13/t1197578390prdjlx0yquvpgdc/29h8p1197579284.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/13/t1197578390prdjlx0yquvpgdc/29h8p1197579284.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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