ACF 8
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 2 seconds |
| R Server | 'Gwilym Jenkins' @ 72.249.127.135 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 8.8882 | 0 |
| 1 | 0.134468 | 1.1952 | 0.117796 |
| 2 | -0.10643 | -0.946 | 0.826477 |
| 3 | -0.082667 | -0.7348 | 0.76767 |
| 4 | 0.075642 | 0.6723 | 0.251671 |
| 5 | -0.032009 | -0.2845 | 0.611615 |
| 6 | 0.0603 | 0.536 | 0.296747 |
| 7 | -0.01681 | -0.1494 | 0.559196 |
| 8 | -0.350335 | -3.1138 | 0.998714 |
| 9 | -0.085744 | -0.7621 | 0.775867 |
| 10 | 0.148794 | 1.3225 | 0.094907 |
| 11 | 0.160109 | 1.4231 | 0.079325 |
| 12 | -0.092345 | -0.8208 | 0.792878 |
| 13 | 0.034705 | 0.3085 | 0.379269 |
| 14 | -0.084271 | -0.749 | 0.771964 |
| 15 | -0.097821 | -0.8694 | 0.806382 |
| 16 | -0.05213 | -0.4633 | 0.677804 |
| 17 | 0.012177 | 0.1082 | 0.457043 |
| 18 | -0.025286 | -0.2247 | 0.588622 |
| 19 | -0.016264 | -0.1446 | 0.557287 |
| 20 | 0.204034 | 1.8135 | 0.036776 |
| 21 | 0.085708 | 0.7618 | 0.224226 |
| 22 | 0.052832 | 0.4696 | 0.319972 |
| 23 | -0.080245 | -0.7132 | 0.761098 |
| 24 | 0.183876 | 1.6343 | 0.053085 |
| 25 | 0.053029 | 0.4713 | 0.319353 |
| 26 | -0.057228 | -0.5087 | 0.693795 |
| 27 | -0.205055 | -1.8226 | 0.963924 |
| 28 | -0.188755 | -1.6777 | 0.95132 |
| 29 | -0.101943 | -0.9061 | 0.816177 |
| 30 | 0.058022 | 0.5157 | 0.303748 |
| 31 | 0.088378 | 0.7855 | 0.21725 |
| 32 | -0.118806 | -1.056 | 0.8529 |
| 33 | -0.09401 | -0.8356 | 0.797045 |
| 34 | -0.044813 | -0.3983 | 0.654262 |
| 35 | 0.108989 | 0.9687 | 0.167822 |
| 36 | 0.050427 | 0.4482 | 0.327617 |
| 37 | 0.017751 | 0.1578 | 0.437518 |
| 38 | -0.052378 | -0.4655 | 0.678588 |
| 39 | -0.04148 | -0.3687 | 0.643326 |
| 40 | 0.017584 | 0.1563 | 0.4381 |
| 41 | 0.111565 | 0.9916 | 0.162207 |
| 42 | 0.124619 | 1.1076 | 0.13569 |
| 43 | -0.036977 | -0.3287 | 0.628359 |
| 44 | -0.04176 | -0.3712 | 0.64425 |
| 45 | 0.04283 | 0.3807 | 0.35223 |
| 46 | 0.00889 | 0.079 | 0.46861 |
| 47 | -0.081876 | -0.7277 | 0.765535 |
| 48 | -0.045475 | -0.4042 | 0.656418 |
| 49 | -0.035949 | -0.3195 | 0.624911 |
| 50 | -0.081432 | -0.7238 | 0.764333 |
| 51 | -0.030695 | -0.2728 | 0.607148 |
| 52 | 0.009199 | 0.0818 | 0.467523 |
| 53 | -0.041321 | -0.3673 | 0.6428 |
| 54 | -0.046884 | -0.4167 | 0.66099 |
| 55 | 0.022677 | 0.2016 | 0.420389 |
| 56 | -0.009014 | -0.0801 | 0.531826 |
| 57 | -0.021484 | -0.191 | 0.575476 |
| 58 | 0.038585 | 0.343 | 0.366273 |
| 59 | 0.058607 | 0.5209 | 0.301943 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.134468 | 1.1952 | 0.117796 |
| 1 | -0.126805 | -1.1271 | 0.868437 |
| 2 | -0.051225 | -0.4553 | 0.674927 |
| 3 | 0.084941 | 0.755 | 0.226255 |
| 4 | -0.073693 | -0.655 | 0.742815 |
| 5 | 0.092575 | 0.8228 | 0.206542 |
| 6 | -0.040962 | -0.3641 | 0.641612 |
| 7 | -0.362485 | -3.2218 | 0.999075 |
| 8 | 0.048809 | 0.4338 | 0.3328 |
| 9 | 0.084087 | 0.7474 | 0.228526 |
| 10 | 0.081908 | 0.728 | 0.234378 |
| 11 | -0.053947 | -0.4795 | 0.683544 |
| 12 | 0.060027 | 0.5335 | 0.297581 |
| 13 | -0.101451 | -0.9017 | 0.815025 |
| 14 | -0.10341 | -0.9191 | 0.819586 |
| 15 | -0.153591 | -1.3651 | 0.911959 |
| 16 | -0.049829 | -0.4429 | 0.670473 |
| 17 | 0.084509 | 0.7511 | 0.227403 |
| 18 | 0.078454 | 0.6973 | 0.243827 |
| 19 | 0.205955 | 1.8306 | 0.035468 |
| 20 | 0.067077 | 0.5962 | 0.276376 |
| 21 | 0.008795 | 0.0782 | 0.468944 |
| 22 | -0.190261 | -1.6911 | 0.952618 |
| 23 | 0.123987 | 1.102 | 0.136899 |
| 24 | 0.038163 | 0.3392 | 0.36768 |
| 25 | -0.037497 | -0.3333 | 0.630098 |
| 26 | -0.115493 | -1.0265 | 0.846111 |
| 27 | -0.10046 | -0.8929 | 0.812691 |
| 28 | -0.059896 | -0.5324 | 0.702016 |
| 29 | 0.006721 | 0.0597 | 0.476259 |
| 30 | -0.084577 | -0.7517 | 0.772779 |
| 31 | -0.027765 | -0.2468 | 0.59714 |
| 32 | 0.013202 | 0.1173 | 0.453444 |
| 33 | -0.064423 | -0.5726 | 0.715731 |
| 34 | -0.027046 | -0.2404 | 0.594674 |
| 35 | 0.021956 | 0.1951 | 0.42289 |
| 36 | -0.019275 | -0.1713 | 0.567796 |
| 37 | 0.075163 | 0.6681 | 0.25302 |
| 38 | 0.038899 | 0.3457 | 0.365229 |
| 39 | -0.034005 | -0.3022 | 0.61837 |
| 40 | 0.032481 | 0.2887 | 0.386784 |
| 41 | 0.001797 | 0.016 | 0.493649 |
| 42 | -0.068911 | -0.6125 | 0.729015 |
| 43 | -0.075888 | -0.6745 | 0.749022 |
| 44 | 0.06892 | 0.6126 | 0.270958 |
| 45 | -0.073957 | -0.6573 | 0.743566 |
| 46 | 0.021082 | 0.1874 | 0.425921 |
| 47 | -0.025954 | -0.2307 | 0.590922 |
| 48 | -0.007665 | -0.0681 | 0.527071 |
| 49 | -0.043287 | -0.3847 | 0.649269 |
| 50 | -0.017082 | -0.1518 | 0.560145 |
| 51 | 0.002355 | 0.0209 | 0.491678 |
| 52 | 0.045583 | 0.4051 | 0.343232 |
| 53 | -0.059405 | -0.528 | 0.700512 |
| 54 | -0.126189 | -1.1216 | 0.867284 |
| 55 | -0.051915 | -0.4614 | 0.677121 |
| 56 | 0.007196 | 0.064 | 0.474583 |
| 57 | 0.040613 | 0.361 | 0.359541 |
| 58 | 0.041448 | 0.3684 | 0.356781 |
| 59 | -0.01387 | -0.1233 | 0.548901 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/25/t1198585469thc02jbibu582p4/22qgu1198586630.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/25/t1198585469thc02jbibu582p4/22qgu1198586630.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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