ws 7 Q2 T
| 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 | 8.2462 | 0 |
| 1 | 0.214137 | 1.7658 | 0.040958 |
| 2 | 0.390237 | 3.218 | 0.000989 |
| 3 | 0.122373 | 1.0091 | 0.158249 |
| 4 | 0.150911 | 1.2444 | 0.108804 |
| 5 | 0.270046 | 2.2269 | 0.014636 |
| 6 | 0.194583 | 1.6046 | 0.056611 |
| 7 | 0.006943 | 0.0572 | 0.477257 |
| 8 | 0.133289 | 1.0991 | 0.137795 |
| 9 | 0.082767 | 0.6825 | 0.248615 |
| 10 | -0.046199 | -0.381 | 0.647794 |
| 11 | 0.035941 | 0.2964 | 0.383922 |
| 12 | -0.388276 | -3.2018 | 0.998961 |
| 13 | 0.003176 | 0.0262 | 0.48959 |
| 14 | -0.143006 | -1.1793 | 0.878798 |
| 15 | 0.022863 | 0.1885 | 0.425512 |
| 16 | -0.067112 | -0.5534 | 0.709105 |
| 17 | -0.099437 | -0.82 | 0.792453 |
| 18 | -0.035315 | -0.2912 | 0.614114 |
| 19 | 0.026595 | 0.2193 | 0.413533 |
| 20 | -0.063697 | -0.5253 | 0.699445 |
| 21 | -0.002837 | -0.0234 | 0.509297 |
| 22 | -0.135607 | -1.1182 | 0.866302 |
| 23 | -0.027448 | -0.2263 | 0.589193 |
| 24 | 0.061372 | 0.5061 | 0.307216 |
| 25 | -0.069814 | -0.5757 | 0.716642 |
| 26 | 0.080407 | 0.6631 | 0.254769 |
| 27 | -0.05523 | -0.4554 | 0.674877 |
| 28 | 0.007424 | 0.0612 | 0.475681 |
| 29 | -0.014601 | -0.1204 | 0.547742 |
| 30 | -0.097873 | -0.8071 | 0.788784 |
| 31 | -0.164034 | -1.3527 | 0.909677 |
| 32 | -0.013898 | -0.1146 | 0.545452 |
| 33 | -0.079183 | -0.653 | 0.742009 |
| 34 | 0.100972 | 0.8326 | 0.203981 |
| 35 | -0.016924 | -0.1396 | 0.55529 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.214137 | 1.7658 | 0.040958 |
| 1 | 0.360932 | 2.9763 | 0.002019 |
| 2 | -0.010025 | -0.0827 | 0.53282 |
| 3 | -0.006648 | -0.0548 | 0.521778 |
| 4 | 0.25213 | 2.0791 | 0.020691 |
| 5 | 0.097318 | 0.8025 | 0.212528 |
| 6 | -0.268567 | -2.2147 | 0.984931 |
| 7 | 0.082884 | 0.6835 | 0.248315 |
| 8 | 0.194911 | 1.6073 | 0.056314 |
| 9 | -0.328014 | -2.7049 | 0.995686 |
| 10 | -0.094868 | -0.7823 | 0.781625 |
| 11 | -0.266562 | -2.1981 | 0.984326 |
| 12 | 0.143883 | 1.1865 | 0.119779 |
| 13 | 0.020896 | 0.1723 | 0.431851 |
| 14 | 0.041447 | 0.3418 | 0.366786 |
| 15 | 0.033898 | 0.2795 | 0.390345 |
| 16 | 0.0449 | 0.3703 | 0.35617 |
| 17 | 0.156986 | 1.2945 | 0.099929 |
| 18 | -0.047486 | -0.3916 | 0.651703 |
| 19 | -0.079795 | -0.658 | 0.743623 |
| 20 | 0.100815 | 0.8313 | 0.204346 |
| 21 | -0.247017 | -2.037 | 0.977225 |
| 22 | -0.050152 | -0.4136 | 0.659752 |
| 23 | -0.027444 | -0.2263 | 0.589182 |
| 24 | -0.005897 | -0.0486 | 0.519322 |
| 25 | 0.076355 | 0.6296 | 0.265519 |
| 26 | 0.055334 | 0.4563 | 0.324817 |
| 27 | 0.034942 | 0.2881 | 0.387058 |
| 28 | -0.096561 | -0.7963 | 0.785674 |
| 29 | 0.003224 | 0.0266 | 0.489433 |
| 30 | -0.144454 | -1.1912 | 0.881141 |
| 31 | -0.022449 | -0.1851 | 0.573157 |
| 32 | 0.134001 | 1.105 | 0.136526 |
| 33 | -0.046392 | -0.3826 | 0.64838 |
| 34 | 0.019352 | 0.1596 | 0.436842 |
| 35 | -0.088467 | -0.7295 | 0.765905 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196329841f9w2bhrd3acalai/13vtl1196330459.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196329841f9w2bhrd3acalai/13vtl1196330459.ps (open in new window) |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196329841f9w2bhrd3acalai/2gsfw1196330459.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196329841f9w2bhrd3acalai/2gsfw1196330459.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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