methode2 op tijdreeks2
| 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 | -0.03081 | -0.2387 | 0.593906 |
| 2 | 0.143233 | 1.1095 | 0.135825 |
| 3 | 0.10587 | 0.8201 | 0.207713 |
| 4 | 0.248478 | 1.9247 | 0.029506 |
| 5 | 0.039596 | 0.3067 | 0.380065 |
| 6 | 0.194854 | 1.5093 | 0.068231 |
| 7 | 0.047568 | 0.3685 | 0.356913 |
| 8 | 0.145152 | 1.1243 | 0.132674 |
| 9 | -0.00969 | -0.0751 | 0.529792 |
| 10 | -0.076971 | -0.5962 | 0.723364 |
| 11 | -0.19402 | -1.5029 | 0.930941 |
| 12 | 0.284486 | 2.2036 | 0.0157 |
| 13 | -0.281811 | -2.1829 | 0.983516 |
| 14 | -0.078177 | -0.6056 | 0.726453 |
| 15 | -0.082344 | -0.6378 | 0.736995 |
| 16 | 0.012935 | 0.1002 | 0.460263 |
| 17 | -0.130567 | -1.0114 | 0.842049 |
| 18 | -0.084222 | -0.6524 | 0.741675 |
| 19 | -0.017901 | -0.1387 | 0.55491 |
| 20 | -0.017029 | -0.1319 | 0.552251 |
| 21 | -0.154068 | -1.1934 | 0.881295 |
| 22 | -0.076315 | -0.5911 | 0.721675 |
| 23 | -0.168571 | -1.3057 | 0.901689 |
| 24 | 0.171728 | 1.3302 | 0.094243 |
| 25 | -0.088243 | -0.6835 | 0.751548 |
| 26 | -0.084327 | -0.6532 | 0.741938 |
| 27 | -0.069434 | -0.5378 | 0.703659 |
| 28 | 0.021349 | 0.1654 | 0.434605 |
| 29 | -0.194853 | -1.5093 | 0.931767 |
| 30 | -0.139746 | -1.0825 | 0.858312 |
| 31 | 0.084831 | 0.6571 | 0.256815 |
| 32 | -0.036763 | -0.2848 | 0.611598 |
| 33 | -0.144762 | -1.1213 | 0.86669 |
| 34 | 0.006616 | 0.0512 | 0.479648 |
| 35 | -0.198658 | -1.5388 | 0.935444 |
| 36 | 0.085645 | 0.6634 | 0.254806 |
| 37 | -0.097619 | -0.7562 | 0.773741 |
| 38 | -0.077188 | -0.5979 | 0.72392 |
| 39 | -0.05682 | -0.4401 | 0.669285 |
| 40 | 0.07147 | 0.5536 | 0.290955 |
| 41 | -0.06294 | -0.4875 | 0.686171 |
| 42 | 0.00741 | 0.0574 | 0.477211 |
| 43 | 0.109431 | 0.8476 | 0.200001 |
| 44 | -0.024932 | -0.1931 | 0.576244 |
| 45 | -0.006754 | -0.0523 | 0.520773 |
| 46 | 0.057519 | 0.4455 | 0.328766 |
| 47 | -0.00065 | -0.005 | 0.502001 |
| 48 | 0.102025 | 0.7903 | 0.216238 |
| 49 | 0.021864 | 0.1694 | 0.433043 |
| 50 | 0.019469 | 0.1508 | 0.440316 |
| 51 | 0.043133 | 0.3341 | 0.369733 |
| 52 | 0.048529 | 0.3759 | 0.354157 |
| 53 | 0.002241 | 0.0174 | 0.493104 |
| 54 | 0.011898 | 0.0922 | 0.46344 |
| 55 | 0.064168 | 0.497 | 0.310486 |
| 56 | -0.00331 | -0.0256 | 0.510184 |
| 57 | 0.001174 | 0.0091 | 0.496387 |
| 58 | 0.026837 | 0.2079 | 0.418014 |
| 59 | 0.009986 | 0.0773 | 0.469302 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.03081 | -0.2387 | 0.593906 |
| 1 | 0.142419 | 1.1032 | 0.137178 |
| 2 | 0.116514 | 0.9025 | 0.185197 |
| 3 | 0.244207 | 1.8916 | 0.031686 |
| 4 | 0.038597 | 0.299 | 0.382999 |
| 5 | 0.137628 | 1.0661 | 0.145334 |
| 6 | 0.008709 | 0.0675 | 0.473221 |
| 7 | 0.055252 | 0.428 | 0.335098 |
| 8 | -0.0604 | -0.4679 | 0.679208 |
| 9 | -0.20763 | -1.6083 | 0.94349 |
| 10 | -0.309533 | -2.3976 | 0.990185 |
| 11 | 0.228917 | 1.7732 | 0.040637 |
| 12 | -0.233947 | -1.8121 | 0.962516 |
| 13 | -0.095752 | -0.7417 | 0.769417 |
| 14 | 0.024568 | 0.1903 | 0.424858 |
| 15 | 0.049885 | 0.3864 | 0.350281 |
| 16 | 0.109929 | 0.8515 | 0.198937 |
| 17 | -0.045013 | -0.3487 | 0.635721 |
| 18 | 0.143349 | 1.1104 | 0.135633 |
| 19 | 0.006495 | 0.0503 | 0.480021 |
| 20 | -0.171793 | -1.3307 | 0.905839 |
| 21 | -0.047801 | -0.3703 | 0.643754 |
| 22 | -0.20114 | -1.558 | 0.937757 |
| 23 | 0.000304 | 0.0024 | 0.499066 |
| 24 | 0.111646 | 0.8648 | 0.195295 |
| 25 | -0.108612 | -0.8413 | 0.798241 |
| 26 | 0.005873 | 0.0455 | 0.481933 |
| 27 | -0.002589 | -0.0201 | 0.507968 |
| 28 | -0.14995 | -1.1615 | 0.874982 |
| 29 | -0.102129 | -0.7911 | 0.783995 |
| 30 | 0.018247 | 0.1413 | 0.444036 |
| 31 | -0.010532 | -0.0816 | 0.532375 |
| 32 | -0.075295 | -0.5832 | 0.719039 |
| 33 | 0.042972 | 0.3329 | 0.3702 |
| 34 | -0.076808 | -0.5949 | 0.722943 |
| 35 | 0.010235 | 0.0793 | 0.468538 |
| 36 | -0.009587 | -0.0743 | 0.529476 |
| 37 | -0.016118 | -0.1248 | 0.549469 |
| 38 | -0.084695 | -0.656 | 0.742849 |
| 39 | -0.054501 | -0.4222 | 0.662794 |
| 40 | 0.082704 | 0.6406 | 0.262105 |
| 41 | 0.064792 | 0.5019 | 0.308795 |
| 42 | -0.026726 | -0.207 | 0.581653 |
| 43 | -0.064097 | -0.4965 | 0.68932 |
| 44 | 0.035421 | 0.2744 | 0.392371 |
| 45 | -0.075827 | -0.5874 | 0.720414 |
| 46 | 0.051739 | 0.4008 | 0.345008 |
| 47 | -0.097097 | -0.7521 | 0.772537 |
| 48 | -0.05469 | -0.4236 | 0.663323 |
| 49 | -0.065727 | -0.5091 | 0.693731 |
| 50 | -0.043371 | -0.336 | 0.63096 |
| 51 | -0.007705 | -0.0597 | 0.523696 |
| 52 | 0.001788 | 0.0138 | 0.494499 |
| 53 | 0.115893 | 0.8977 | 0.186465 |
| 54 | 0.008118 | 0.0629 | 0.475035 |
| 55 | -0.055675 | -0.4313 | 0.666086 |
| 56 | 0.009027 | 0.0699 | 0.472243 |
| 57 | -0.046317 | -0.3588 | 0.639486 |
| 58 | -0.084016 | -0.6508 | 0.741165 |
| 59 | NA | NA | NA |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/28/t1196245337wedgkgrqx6wguwr/20k591196245946.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/28/t1196245337wedgkgrqx6wguwr/20k591196245946.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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