ws 7 Q2 V
| 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 | 8.1854 | 0 |
| 1 | -0.410133 | -3.3571 | 0.999349 |
| 2 | -0.167629 | -1.3721 | 0.912696 |
| 3 | 0.098928 | 0.8098 | 0.210472 |
| 4 | 0.02023 | 0.1656 | 0.43449 |
| 5 | 0.028924 | 0.2368 | 0.406785 |
| 6 | -0.013436 | -0.11 | 0.543623 |
| 7 | 0.042995 | 0.3519 | 0.362999 |
| 8 | -0.161405 | -1.3212 | 0.904529 |
| 9 | 0.098856 | 0.8092 | 0.21064 |
| 10 | -0.033716 | -0.276 | 0.608292 |
| 11 | 0.095137 | 0.7787 | 0.219439 |
| 12 | -0.181926 | -1.4891 | 0.929427 |
| 13 | -0.040136 | -0.3285 | 0.628232 |
| 14 | 0.173445 | 1.4197 | 0.080165 |
| 15 | -0.042048 | -0.3442 | 0.634104 |
| 16 | 0.030151 | 0.2468 | 0.402911 |
| 17 | -0.142371 | -1.1654 | 0.875997 |
| 18 | 0.094974 | 0.7774 | 0.21983 |
| 19 | -0.040538 | -0.3318 | 0.62947 |
| 20 | 0.017909 | 0.1466 | 0.441947 |
| 21 | 0.023796 | 0.1948 | 0.423077 |
| 22 | 0.042952 | 0.3516 | 0.36313 |
| 23 | 0.038777 | 0.3174 | 0.375963 |
| 24 | -0.236479 | -1.9357 | 0.971435 |
| 25 | 0.199797 | 1.6354 | 0.053326 |
| 26 | 0.083053 | 0.6798 | 0.249481 |
| 27 | -0.170203 | -1.3932 | 0.915914 |
| 28 | 0.019124 | 0.1565 | 0.438039 |
| 29 | 0.113115 | 0.9259 | 0.178915 |
| 30 | -0.048272 | -0.3951 | 0.652995 |
| 31 | -0.026089 | -0.2135 | 0.584224 |
| 32 | 0.041664 | 0.341 | 0.367072 |
| 33 | -0.101719 | -0.8326 | 0.795987 |
| 34 | 0.030934 | 0.2532 | 0.400444 |
| 35 | 0.083289 | 0.6817 | 0.248874 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.410133 | -3.3571 | 0.999349 |
| 1 | -0.403753 | -3.3049 | 0.999236 |
| 2 | -0.234377 | -1.9185 | 0.970342 |
| 3 | -0.151803 | -1.2426 | 0.89082 |
| 4 | -0.021811 | -0.1785 | 0.570578 |
| 5 | 0.027078 | 0.2216 | 0.412633 |
| 6 | 0.130699 | 1.0698 | 0.144271 |
| 7 | -0.098052 | -0.8026 | 0.787476 |
| 8 | -0.040584 | -0.3322 | 0.629611 |
| 9 | -0.150961 | -1.2357 | 0.889552 |
| 10 | 0.039019 | 0.3194 | 0.375215 |
| 11 | -0.186921 | -1.53 | 0.934639 |
| 12 | -0.262003 | -2.1446 | 0.982192 |
| 13 | -0.138797 | -1.1361 | 0.870019 |
| 14 | -0.071929 | -0.5888 | 0.721 |
| 15 | 0.069143 | 0.566 | 0.286655 |
| 16 | -0.071364 | -0.5841 | 0.719455 |
| 17 | -0.020747 | -0.1698 | 0.567168 |
| 18 | -0.12058 | -0.987 | 0.836401 |
| 19 | -0.192805 | -1.5782 | 0.940382 |
| 20 | -0.215168 | -1.7612 | 0.958618 |
| 21 | -0.05388 | -0.441 | 0.669692 |
| 22 | 0.163346 | 1.337 | 0.092865 |
| 23 | -0.140634 | -1.1511 | 0.873116 |
| 24 | -0.130586 | -1.0689 | 0.855523 |
| 25 | 0.070286 | 0.5753 | 0.283503 |
| 26 | -0.05631 | -0.4609 | 0.676823 |
| 27 | -0.081417 | -0.6664 | 0.746286 |
| 28 | -0.032286 | -0.2643 | 0.60381 |
| 29 | 0.006409 | 0.0525 | 0.479158 |
| 30 | 0.042825 | 0.3505 | 0.363519 |
| 31 | -0.026043 | -0.2132 | 0.584079 |
| 32 | -0.071517 | -0.5854 | 0.719875 |
| 33 | -0.052808 | -0.4322 | 0.666526 |
| 34 | 0.10061 | 0.8235 | 0.206564 |
| 35 | -0.08142 | -0.6664 | 0.746294 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196329118l9amjlu2lf1a65h/1p3do1196329663.png (open in new window) |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196329118l9amjlu2lf1a65h/2vnyh1196329663.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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