Stationarity in time series: Q2
| 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 | 8.3066 | 0 |
| 1 | 0.015245 | 0.1266 | 0.4498 |
| 2 | 0.20797 | 1.7275 | 0.044274 |
| 3 | 0.322259 | 2.6769 | 0.004638 |
| 4 | -0.005969 | -0.0496 | 0.519701 |
| 5 | 0.240266 | 1.9958 | 0.024952 |
| 6 | 0.196965 | 1.6361 | 0.053184 |
| 7 | -0.182698 | -1.5176 | 0.933158 |
| 8 | 0.02419 | 0.2009 | 0.420669 |
| 9 | 0.10584 | 0.8792 | 0.19118 |
| 10 | -0.204896 | -1.702 | 0.953371 |
| 11 | 0.037411 | 0.3108 | 0.378462 |
| 12 | -0.131951 | -1.0961 | 0.86157 |
| 13 | -0.166937 | -1.3867 | 0.914999 |
| 14 | 0.037132 | 0.3084 | 0.379338 |
| 15 | -0.017784 | -0.1477 | 0.558504 |
| 16 | -0.129914 | -1.0791 | 0.857861 |
| 17 | 0.138695 | 1.1521 | 0.12663 |
| 18 | -0.004497 | -0.0374 | 0.514845 |
| 19 | -0.153533 | -1.2753 | 0.896766 |
| 20 | 0.125381 | 1.0415 | 0.150641 |
| 21 | 0.089705 | 0.7451 | 0.229356 |
| 22 | -0.068873 | -0.5721 | 0.715443 |
| 23 | 0.262984 | 2.1845 | 0.016163 |
| 24 | -0.094051 | -0.7812 | 0.781336 |
| 25 | -0.079363 | -0.6592 | 0.744033 |
| 26 | 0.254098 | 2.1107 | 0.019213 |
| 27 | -0.054361 | -0.4516 | 0.673498 |
| 28 | 0.001264 | 0.0105 | 0.495827 |
| 29 | 0.039931 | 0.3317 | 0.370563 |
| 30 | -0.188556 | -1.5663 | 0.939069 |
| 31 | 0.078722 | 0.6539 | 0.25767 |
| 32 | 0.041035 | 0.3409 | 0.367122 |
| 33 | -0.172971 | -1.4368 | 0.922353 |
| 34 | -0.031066 | -0.2581 | 0.601434 |
| 35 | -0.033014 | -0.2742 | 0.607637 |
| 36 | -0.096795 | -0.804 | 0.787932 |
| 37 | 0.110033 | 0.914 | 0.181948 |
| 38 | -0.008393 | -0.0697 | 0.527689 |
| 39 | -0.13564 | -1.1267 | 0.868116 |
| 40 | 0.073681 | 0.612 | 0.271262 |
| 41 | -0.039823 | -0.3308 | 0.6291 |
| 42 | -0.02094 | -0.1739 | 0.56879 |
| 43 | 0.026232 | 0.2179 | 0.414076 |
| 44 | 0.0102 | 0.0847 | 0.466363 |
| 45 | -0.105794 | -0.8788 | 0.808717 |
| 46 | 0.007828 | 0.065 | 0.474171 |
| 47 | -0.07263 | -0.6033 | 0.72586 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.015245 | 0.1266 | 0.4498 |
| 1 | 0.207785 | 1.726 | 0.044412 |
| 2 | 0.330941 | 2.749 | 0.003812 |
| 3 | -0.041238 | -0.3425 | 0.633511 |
| 4 | 0.1222 | 1.0151 | 0.156809 |
| 5 | 0.137525 | 1.1424 | 0.128624 |
| 6 | -0.270425 | -2.2463 | 0.986056 |
| 7 | -0.206554 | -1.7158 | 0.954654 |
| 8 | 0.137412 | 1.1414 | 0.128819 |
| 9 | -0.100036 | -0.831 | 0.795569 |
| 10 | -0.077008 | -0.6397 | 0.737749 |
| 11 | -0.056842 | -0.4722 | 0.680851 |
| 12 | 0.035683 | 0.2964 | 0.383906 |
| 13 | -0.001285 | -0.0107 | 0.504244 |
| 14 | 0.098628 | 0.8193 | 0.207729 |
| 15 | 0.015049 | 0.125 | 0.450441 |
| 16 | 0.147737 | 1.2272 | 0.11196 |
| 17 | 0.057188 | 0.475 | 0.31813 |
| 18 | -0.250911 | -2.0842 | 0.979578 |
| 19 | -0.092532 | -0.7686 | 0.77763 |
| 20 | 0.29953 | 2.4881 | 0.007631 |
| 21 | -0.074266 | -0.6169 | 0.730334 |
| 22 | 0.046547 | 0.3867 | 0.350102 |
| 23 | 0.000692 | 0.0057 | 0.497716 |
| 24 | -0.103285 | -0.858 | 0.803055 |
| 25 | -0.011441 | -0.095 | 0.53772 |
| 26 | 0.101926 | 0.8467 | 0.200056 |
| 27 | 0.027435 | 0.2279 | 0.410203 |
| 28 | -0.116066 | -0.9641 | 0.830822 |
| 29 | -0.130863 | -1.087 | 0.859596 |
| 30 | 0.078754 | 0.6542 | 0.257586 |
| 31 | -0.058245 | -0.4838 | 0.684977 |
| 32 | 0.042504 | 0.3531 | 0.362558 |
| 33 | -0.01633 | -0.1356 | 0.553751 |
| 34 | 0.044327 | 0.3682 | 0.356922 |
| 35 | 0.018198 | 0.1512 | 0.440144 |
| 36 | 0.052507 | 0.4362 | 0.332042 |
| 37 | 0.005733 | 0.0476 | 0.481079 |
| 38 | -0.031392 | -0.2608 | 0.602474 |
| 39 | -0.05755 | -0.478 | 0.682935 |
| 40 | -0.102416 | -0.8507 | 0.801069 |
| 41 | 0.023985 | 0.1992 | 0.421334 |
| 42 | -0.02867 | -0.2382 | 0.593766 |
| 43 | -0.040369 | -0.3353 | 0.630803 |
| 44 | 0.025173 | 0.2091 | 0.417492 |
| 45 | -0.055059 | -0.4574 | 0.675574 |
| 46 | -0.091062 | -0.7564 | 0.774013 |
| 47 | -0.064049 | -0.532 | 0.701794 |
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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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