Melkprijs d=0 & D=0
| 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 | 7.746 | 0 |
| 1 | 0.858108 | 6.6469 | 0 |
| 2 | 0.72973 | 5.6525 | 0 |
| 3 | 0.608108 | 4.7104 | 8e-06 |
| 4 | 0.493243 | 3.8206 | 0.000159 |
| 5 | 0.358108 | 2.7739 | 0.003686 |
| 6 | 0.216216 | 1.6748 | 0.049589 |
| 7 | 0.135135 | 1.0468 | 0.149706 |
| 8 | 0.087838 | 0.6804 | 0.249438 |
| 9 | 0.074324 | 0.5757 | 0.283481 |
| 10 | 0.060811 | 0.471 | 0.319661 |
| 11 | 0.047297 | 0.3664 | 0.357691 |
| 12 | 0.013514 | 0.1047 | 0.458491 |
| 13 | 0.006757 | 0.0523 | 0.479217 |
| 14 | -0.013514 | -0.1047 | 0.541509 |
| 15 | -0.033784 | -0.2617 | 0.602771 |
| 16 | -0.060811 | -0.471 | 0.680339 |
| 17 | -0.087838 | -0.6804 | 0.750562 |
| 18 | -0.081081 | -0.6281 | 0.733823 |
| 19 | -0.101351 | -0.7851 | 0.782248 |
| 20 | -0.094595 | -0.7327 | 0.766711 |
| 21 | -0.121622 | -0.9421 | 0.825034 |
| 22 | -0.114865 | -0.8897 | 0.81142 |
| 23 | -0.114865 | -0.8897 | 0.81142 |
| 24 | -0.108108 | -0.8374 | 0.797155 |
| 25 | -0.108108 | -0.8374 | 0.797155 |
| 26 | -0.114865 | -0.8897 | 0.81142 |
| 27 | -0.108108 | -0.8374 | 0.797155 |
| 28 | -0.108108 | -0.8374 | 0.797155 |
| 29 | -0.081081 | -0.6281 | 0.733823 |
| 30 | -0.060811 | -0.471 | 0.680339 |
| 31 | -0.040541 | -0.314 | 0.622705 |
| 32 | -0.02027 | -0.157 | 0.562119 |
| 33 | 0.006757 | 0.0523 | 0.479217 |
| 34 | 0.033784 | 0.2617 | 0.397229 |
| 35 | 0.027027 | 0.2094 | 0.417442 |
| 36 | 0.013514 | 0.1047 | 0.458491 |
| 37 | -0.006757 | -0.0523 | 0.520783 |
| 38 | -0.027027 | -0.2094 | 0.582558 |
| 39 | -0.054054 | -0.4187 | 0.661535 |
| 40 | -0.067568 | -0.5234 | 0.69868 |
| 41 | -0.101351 | -0.7851 | 0.782248 |
| 42 | -0.135135 | -1.0468 | 0.850294 |
| 43 | -0.168919 | -1.3084 | 0.902143 |
| 44 | -0.162162 | -1.2561 | 0.893026 |
| 45 | -0.162162 | -1.2561 | 0.893026 |
| 46 | -0.195946 | -1.5178 | 0.932841 |
| 47 | -0.195946 | -1.5178 | 0.932841 |
| 48 | -0.195946 | -1.5178 | 0.932841 |
| 49 | -0.195946 | -1.5178 | 0.932841 |
| 50 | -0.195946 | -1.5178 | 0.932841 |
| 51 | -0.189189 | -1.4655 | 0.925991 |
| 52 | -0.175676 | -1.3608 | 0.910663 |
| 53 | -0.148649 | -1.1514 | 0.872938 |
| 54 | -0.121622 | -0.9421 | 0.825034 |
| 55 | -0.094595 | -0.7327 | 0.766711 |
| 56 | -0.067568 | -0.5234 | 0.69868 |
| 57 | -0.033784 | -0.2617 | 0.602771 |
| 58 | 0 | 0 | 0.5 |
| 59 | 0 | 0 | 0.5 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.858108 | 6.6469 | 0 |
| 1 | -0.025108 | -0.1945 | 0.576774 |
| 2 | -0.046514 | -0.3603 | 0.640055 |
| 3 | -0.047896 | -0.371 | 0.644028 |
| 4 | -0.151862 | -1.1763 | 0.877943 |
| 5 | -0.130661 | -1.0121 | 0.842222 |
| 6 | 0.11894 | 0.9213 | 0.180291 |
| 7 | 0.071414 | 0.5532 | 0.291101 |
| 8 | 0.100636 | 0.7795 | 0.219367 |
| 9 | -0.005711 | -0.0442 | 0.517568 |
| 10 | -0.062832 | -0.4867 | 0.685875 |
| 11 | -0.161476 | -1.2508 | 0.892066 |
| 12 | 0.050647 | 0.3923 | 0.348111 |
| 13 | -0.039953 | -0.3095 | 0.620983 |
| 14 | 0.037201 | 0.2882 | 0.387111 |
| 15 | -0.001032 | -0.008 | 0.503175 |
| 16 | -0.036174 | -0.2802 | 0.609856 |
| 17 | 0.049011 | 0.3796 | 0.352776 |
| 18 | -0.113523 | -0.8793 | 0.80864 |
| 19 | 0.053402 | 0.4136 | 0.340303 |
| 20 | -0.127925 | -0.9909 | 0.837143 |
| 21 | 0.08398 | 0.6505 | 0.258923 |
| 22 | -0.028867 | -0.2236 | 0.588088 |
| 23 | 0.034838 | 0.2699 | 0.394098 |
| 24 | -0.035807 | -0.2774 | 0.608773 |
| 25 | -0.03183 | -0.2466 | 0.596951 |
| 26 | -0.019131 | -0.1482 | 0.558655 |
| 27 | -0.022252 | -0.1724 | 0.568135 |
| 28 | 0.088335 | 0.6842 | 0.248229 |
| 29 | 0.047992 | 0.3717 | 0.355697 |
| 30 | -0.020494 | -0.1587 | 0.562799 |
| 31 | 0.029242 | 0.2265 | 0.410787 |
| 32 | -0.038931 | -0.3016 | 0.617985 |
| 33 | 0.02499 | 0.1936 | 0.423584 |
| 34 | -0.104368 | -0.8084 | 0.788982 |
| 35 | -0.01014 | -0.0785 | 0.53117 |
| 36 | -0.009418 | -0.073 | 0.528956 |
| 37 | -0.043942 | -0.3404 | 0.632617 |
| 38 | 0.034394 | 0.2664 | 0.395417 |
| 39 | -0.010882 | -0.0843 | 0.533449 |
| 40 | -0.074468 | -0.5768 | 0.716893 |
| 41 | -0.120522 | -0.9336 | 0.822863 |
| 42 | -0.064362 | -0.4985 | 0.690039 |
| 43 | 0.107298 | 0.8311 | 0.204598 |
| 44 | -0.017561 | -0.136 | 0.553874 |
| 45 | -0.079882 | -0.6188 | 0.730794 |
| 46 | 0.029534 | 0.2288 | 0.409912 |
| 47 | -0.068127 | -0.5277 | 0.700177 |
| 48 | -0.093637 | -0.7253 | 0.764459 |
| 49 | 0.028936 | 0.2241 | 0.411705 |
| 50 | 0.042163 | 0.3266 | 0.372556 |
| 51 | -0.010691 | -0.0828 | 0.532861 |
| 52 | 0.095327 | 0.7384 | 0.231574 |
| 53 | -0.046794 | -0.3625 | 0.640861 |
| 54 | -0.016083 | -0.1246 | 0.549364 |
| 55 | -0.009709 | -0.0752 | 0.529849 |
| 56 | 0.037541 | 0.2908 | 0.386108 |
| 57 | -0.004738 | -0.0367 | 0.514577 |
| 58 | -0.06348 | -0.4917 | 0.687641 |
| 59 | NA | NA | NA |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196366894a9ytikxmpopa9z6/2uh1w1196367276.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196366894a9ytikxmpopa9z6/2uh1w1196367276.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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