Autocorrelation Function 4 d=1 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 | 7.6811 | 0 |
| 1 | -0.119298 | -0.9163 | 0.818392 |
| 2 | -0.217671 | -1.672 | 0.950086 |
| 3 | 0.123525 | 0.9488 | 0.173294 |
| 4 | 0.007258 | 0.0557 | 0.477866 |
| 5 | -0.198442 | -1.5243 | 0.933607 |
| 6 | -0.110358 | -0.8477 | 0.799979 |
| 7 | -0.155707 | -1.196 | 0.881761 |
| 8 | 0.014415 | 0.1107 | 0.456107 |
| 9 | 0.037285 | 0.2864 | 0.387792 |
| 10 | -0.098366 | -0.7556 | 0.773541 |
| 11 | -0.08079 | -0.6206 | 0.731361 |
| 12 | 0.700071 | 5.3773 | 1e-06 |
| 13 | -0.045738 | -0.3513 | 0.636699 |
| 14 | -0.196123 | -1.5064 | 0.931356 |
| 15 | 0.119024 | 0.9142 | 0.182156 |
| 16 | 0.041536 | 0.319 | 0.375409 |
| 17 | -0.171089 | -1.3142 | 0.903061 |
| 18 | -0.098531 | -0.7568 | 0.773918 |
| 19 | -0.144901 | -1.113 | 0.86489 |
| 20 | 0.008079 | 0.0621 | 0.475363 |
| 21 | 0.053573 | 0.4115 | 0.341096 |
| 22 | -0.114009 | -0.8757 | 0.807633 |
| 23 | -0.078438 | -0.6025 | 0.725423 |
| 24 | 0.504279 | 3.8734 | 0.000136 |
| 25 | -0.022577 | -0.1734 | 0.568541 |
| 26 | -0.149764 | -1.1504 | 0.872682 |
| 27 | 0.117826 | 0.905 | 0.184563 |
| 28 | 0.007789 | 0.0598 | 0.476247 |
| 29 | -0.10413 | -0.7998 | 0.786494 |
| 30 | -0.059549 | -0.4574 | 0.675469 |
| 31 | -0.071908 | -0.5523 | 0.708597 |
| 32 | -0.059796 | -0.4593 | 0.676147 |
| 33 | 0.011499 | 0.0883 | 0.46496 |
| 34 | -0.058725 | -0.4511 | 0.673205 |
| 35 | -0.05937 | -0.456 | 0.674978 |
| 36 | 0.350188 | 2.6898 | 0.004641 |
| 37 | 0.000915 | 0.007 | 0.497207 |
| 38 | -0.105512 | -0.8105 | 0.789532 |
| 39 | 0.067146 | 0.5158 | 0.303975 |
| 40 | -0.031603 | -0.2427 | 0.595477 |
| 41 | -0.030795 | -0.2365 | 0.593083 |
| 42 | -0.043847 | -0.3368 | 0.631268 |
| 43 | -0.043057 | -0.3307 | 0.628988 |
| 44 | -0.028908 | -0.222 | 0.587477 |
| 45 | 0.006413 | 0.0493 | 0.480438 |
| 46 | -0.006783 | -0.0521 | 0.520689 |
| 47 | -0.035714 | -0.2743 | 0.607603 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.119298 | -0.9163 | 0.818392 |
| 1 | -0.235251 | -1.807 | 0.962069 |
| 2 | 0.068065 | 0.5228 | 0.30153 |
| 3 | -0.018795 | -0.1444 | 0.55715 |
| 4 | -0.16957 | -1.3025 | 0.901096 |
| 5 | -0.186277 | -1.4308 | 0.921122 |
| 6 | -0.314759 | -2.4177 | 0.990637 |
| 7 | -0.136659 | -1.0497 | 0.85093 |
| 8 | -0.108604 | -0.8342 | 0.796234 |
| 9 | -0.208951 | -1.605 | 0.943081 |
| 10 | -0.338847 | -2.6027 | 0.994161 |
| 11 | 0.570356 | 4.381 | 2.5e-05 |
| 12 | 0.088168 | 0.6772 | 0.250454 |
| 13 | 0.108429 | 0.8329 | 0.204141 |
| 14 | -0.02188 | -0.1681 | 0.566447 |
| 15 | 0.058534 | 0.4496 | 0.32732 |
| 16 | 0.09695 | 0.7447 | 0.229709 |
| 17 | 0.070048 | 0.538 | 0.296284 |
| 18 | -0.003809 | -0.0293 | 0.51162 |
| 19 | -0.019896 | -0.1528 | 0.560471 |
| 20 | 0.13374 | 1.0273 | 0.154241 |
| 21 | -0.09943 | -0.7637 | 0.775966 |
| 22 | -0.056109 | -0.431 | 0.665972 |
| 23 | -0.098698 | -0.7581 | 0.774299 |
| 24 | -0.074131 | -0.5694 | 0.714381 |
| 25 | -0.014333 | -0.1101 | 0.543644 |
| 26 | -0.036391 | -0.2795 | 0.60959 |
| 27 | -0.165757 | -1.2732 | 0.89603 |
| 28 | -0.02703 | -0.2076 | 0.581881 |
| 29 | 0.001998 | 0.0153 | 0.493904 |
| 30 | 0.137291 | 1.0546 | 0.147964 |
| 31 | -0.09451 | -0.7259 | 0.764629 |
| 32 | -0.120904 | -0.9287 | 0.821581 |
| 33 | 0.00721 | 0.0554 | 0.478012 |
| 34 | 0.099349 | 0.7631 | 0.224217 |
| 35 | 0.080162 | 0.6157 | 0.270217 |
| 36 | -0.033218 | -0.2552 | 0.600253 |
| 37 | 0.039394 | 0.3026 | 0.381634 |
| 38 | -0.075418 | -0.5793 | 0.717703 |
| 39 | -0.023642 | -0.1816 | 0.571739 |
| 40 | -0.069881 | -0.5368 | 0.703276 |
| 41 | -0.096658 | -0.7424 | 0.769619 |
| 42 | -0.022967 | -0.1764 | 0.569714 |
| 43 | 0.092078 | 0.7073 | 0.241094 |
| 44 | 0.045784 | 0.3517 | 0.363169 |
| 45 | 0.045261 | 0.3477 | 0.364668 |
| 46 | 0.008062 | 0.0619 | 0.475415 |
| 47 | -0.135047 | -1.0373 | 0.848089 |
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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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