Workshop 3, Q2
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 1 seconds |
| R Server | 'Gwilym Jenkins' @ 72.249.127.135 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 8.2462 | 0 |
| 1 | -0.581159 | -4.7924 | 0.999995 |
| 2 | 0.011966 | 0.0987 | 0.460843 |
| 3 | 0.298501 | 2.4615 | 0.008189 |
| 4 | -0.226911 | -1.8712 | 0.967187 |
| 5 | 0.045615 | 0.3762 | 0.353987 |
| 6 | 0.164487 | 1.3564 | 0.089731 |
| 7 | -0.210023 | -1.7319 | 0.956087 |
| 8 | 0.017355 | 0.1431 | 0.443311 |
| 9 | 0.163465 | 1.348 | 0.091071 |
| 10 | -0.255585 | -2.1076 | 0.980623 |
| 11 | 0.191717 | 1.5809 | 0.059266 |
| 12 | -0.121705 | -1.0036 | 0.840436 |
| 13 | -0.074663 | -0.6157 | 0.729921 |
| 14 | 0.12622 | 1.0408 | 0.150819 |
| 15 | 0.00348 | 0.0287 | 0.488595 |
| 16 | -0.20949 | -1.7275 | 0.955691 |
| 17 | 0.185508 | 1.5297 | 0.065361 |
| 18 | 0.039965 | 0.3296 | 0.371372 |
| 19 | -0.231288 | -1.9073 | 0.969643 |
| 20 | 0.244345 | 2.0149 | 0.023934 |
| 21 | -0.054051 | -0.4457 | 0.671391 |
| 22 | -0.185727 | -1.5315 | 0.934863 |
| 23 | 0.315661 | 2.603 | 0.005668 |
| 24 | -0.140681 | -1.1601 | 0.874965 |
| 25 | -0.125534 | -1.0352 | 0.847873 |
| 26 | 0.220655 | 1.8196 | 0.036614 |
| 27 | -0.116346 | -0.9594 | 0.829625 |
| 28 | -0.026798 | -0.221 | 0.587114 |
| 29 | 0.198313 | 1.6353 | 0.053301 |
| 30 | -0.320778 | -2.6452 | 0.994934 |
| 31 | 0.212897 | 1.7556 | 0.041831 |
| 32 | 0.037865 | 0.3122 | 0.377906 |
| 33 | -0.181006 | -1.4926 | 0.929918 |
| 34 | 0.129256 | 1.0659 | 0.145125 |
| 35 | -0.019373 | -0.1598 | 0.563226 |
| 36 | -0.079629 | -0.6566 | 0.743186 |
| 37 | 0.089041 | 0.7343 | 0.232659 |
| 38 | 0.033791 | 0.2786 | 0.390682 |
| 39 | -0.178659 | -1.4733 | 0.927353 |
| 40 | 0.187751 | 1.5482 | 0.063104 |
| 41 | -0.07603 | -0.627 | 0.733606 |
| 42 | -0.021635 | -0.1784 | 0.570533 |
| 43 | 0.0167 | 0.1377 | 0.445439 |
| 44 | 0.024008 | 0.198 | 0.421827 |
| 45 | -0.041317 | -0.3407 | 0.632813 |
| 46 | 0.015758 | 0.1299 | 0.448496 |
| 47 | 0.07008 | 0.5779 | 0.282623 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.581159 | -4.7924 | 0.999995 |
| 1 | -0.491926 | -4.0565 | 0.999935 |
| 2 | 0.045796 | 0.3776 | 0.353437 |
| 3 | 0.114195 | 0.9417 | 0.174846 |
| 4 | 0.074907 | 0.6177 | 0.269418 |
| 5 | 0.204045 | 1.6826 | 0.04852 |
| 6 | 0.048069 | 0.3964 | 0.346531 |
| 7 | -0.20515 | -1.6917 | 0.95236 |
| 8 | -0.103218 | -0.8512 | 0.801165 |
| 9 | -0.217558 | -1.794 | 0.961373 |
| 10 | -0.003248 | -0.0268 | 0.510644 |
| 11 | -0.118424 | -0.9765 | 0.833872 |
| 12 | -0.187575 | -1.5468 | 0.936722 |
| 13 | -0.154737 | -1.276 | 0.896851 |
| 14 | 0.127458 | 1.051 | 0.148479 |
| 15 | -0.047047 | -0.388 | 0.650371 |
| 16 | -0.097836 | -0.8068 | 0.788696 |
| 17 | 0.143576 | 1.184 | 0.120275 |
| 18 | 0.001675 | 0.0138 | 0.494511 |
| 19 | -0.071392 | -0.5887 | 0.720997 |
| 20 | 0.040949 | 0.3377 | 0.368324 |
| 21 | -0.167718 | -1.383 | 0.914411 |
| 22 | 0.016913 | 0.1395 | 0.444747 |
| 23 | 0.067733 | 0.5585 | 0.289156 |
| 24 | -0.057747 | -0.4762 | 0.682267 |
| 25 | -0.133798 | -1.1033 | 0.863113 |
| 26 | -0.033079 | -0.2728 | 0.607075 |
| 27 | -0.019473 | -0.1606 | 0.563548 |
| 28 | 0.156513 | 1.2906 | 0.100599 |
| 29 | -0.094454 | -0.7789 | 0.780626 |
| 30 | -0.022088 | -0.1821 | 0.571992 |
| 31 | -0.033436 | -0.2757 | 0.6082 |
| 32 | 0.051494 | 0.4246 | 0.336224 |
| 33 | -0.014014 | -0.1156 | 0.54583 |
| 34 | -0.046712 | -0.3852 | 0.649355 |
| 35 | 0.022225 | 0.1833 | 0.427565 |
| 36 | -0.015966 | -0.1317 | 0.552179 |
| 37 | -0.034494 | -0.2844 | 0.611534 |
| 38 | -0.006616 | -0.0546 | 0.521674 |
| 39 | 0.054199 | 0.4469 | 0.328171 |
| 40 | -0.023025 | -0.1899 | 0.575012 |
| 41 | -0.022897 | -0.1888 | 0.574599 |
| 42 | -0.118379 | -0.9762 | 0.833782 |
| 43 | -0.068354 | -0.5637 | 0.712581 |
| 44 | 0.10423 | 0.8595 | 0.196541 |
| 45 | -0.074235 | -0.6122 | 0.728762 |
| 46 | 0.062785 | 0.5177 | 0.30316 |
| 47 | 0.09218 | 0.7601 | 0.2249 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/27/t1196159305ir2sqz42gwb88ih/1p5el1196159827.ps (open in new window) |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/27/t1196159305ir2sqz42gwb88ih/2dxin1196159827.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/27/t1196159305ir2sqz42gwb88ih/2dxin1196159827.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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