workshop3
| 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 | 9.6954 | 0 |
| 1 | 0.583299 | 5.6553 | 0 |
| 2 | 0.641052 | 6.2152 | 0 |
| 3 | 0.58201 | 5.6428 | 0 |
| 4 | 0.462105 | 4.4803 | 1e-05 |
| 5 | 0.453488 | 4.3967 | 1.4e-05 |
| 6 | 0.383931 | 3.7224 | 0.000168 |
| 7 | 0.314097 | 3.0453 | 0.001508 |
| 8 | 0.307036 | 2.9768 | 0.001852 |
| 9 | 0.264062 | 2.5602 | 0.006028 |
| 10 | 0.10873 | 1.0542 | 0.147253 |
| 11 | 0.117529 | 1.1395 | 0.128697 |
| 12 | -0.031762 | -0.3079 | 0.620597 |
| 13 | 0.057958 | 0.5619 | 0.287754 |
| 14 | 0.073194 | 0.7096 | 0.23984 |
| 15 | 0.078024 | 0.7565 | 0.225629 |
| 16 | 0.070535 | 0.6839 | 0.247874 |
| 17 | 0.092721 | 0.899 | 0.185485 |
| 18 | 0.146063 | 1.4161 | 0.080021 |
| 19 | -0.004397 | -0.0426 | 0.516955 |
| 20 | 0.085663 | 0.8305 | 0.204171 |
| 21 | 0.003344 | 0.0324 | 0.487103 |
| 22 | 0.039548 | 0.3834 | 0.351131 |
| 23 | 0.095804 | 0.9289 | 0.177672 |
| 24 | -0.007096 | -0.0688 | 0.52735 |
| 25 | -0.036786 | -0.3567 | 0.638924 |
| 26 | -0.031287 | -0.3033 | 0.618848 |
| 27 | -0.154879 | -1.5016 | 0.931724 |
| 28 | -0.207795 | -2.0147 | 0.976601 |
| 29 | -0.183204 | -1.7762 | 0.960534 |
| 30 | -0.309119 | -2.997 | 0.998257 |
| 31 | -0.245692 | -2.3821 | 0.990385 |
| 32 | -0.296962 | -2.8792 | 0.997531 |
| 33 | -0.30858 | -2.9918 | 0.998229 |
| 34 | -0.388697 | -3.7686 | 0.999857 |
| 35 | -0.365498 | -3.5436 | 0.999692 |
| 36 | -0.376122 | -3.6466 | 0.999782 |
| 37 | -0.346112 | -3.3557 | 0.999428 |
| 38 | -0.303965 | -2.9471 | 0.997977 |
| 39 | -0.32094 | -3.1116 | 0.998768 |
| 40 | -0.190333 | -1.8453 | 0.965932 |
| 41 | -0.226241 | -2.1935 | 0.984631 |
| 42 | -0.240552 | -2.3322 | 0.989089 |
| 43 | -0.161308 | -1.5639 | 0.939404 |
| 44 | -0.188802 | -1.8305 | 0.964828 |
| 45 | -0.182382 | -1.7683 | 0.959869 |
| 46 | -0.087976 | -0.853 | 0.802076 |
| 47 | -0.122049 | -1.1833 | 0.880165 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.583299 | 5.6553 | 0 |
| 1 | 0.455944 | 4.4205 | 1.3e-05 |
| 2 | 0.215501 | 2.0894 | 0.019688 |
| 3 | -0.07937 | -0.7695 | 0.778244 |
| 4 | -0.004283 | -0.0415 | 0.516516 |
| 5 | -0.001313 | -0.0127 | 0.505064 |
| 6 | -0.053619 | -0.5199 | 0.697808 |
| 7 | 0.021899 | 0.2123 | 0.416161 |
| 8 | 0.035824 | 0.3473 | 0.364563 |
| 9 | -0.246289 | -2.3879 | 0.990527 |
| 10 | -0.086453 | -0.8382 | 0.797976 |
| 11 | -0.162065 | -1.5713 | 0.940261 |
| 12 | 0.218472 | 2.1182 | 0.0184 |
| 13 | 0.274775 | 2.664 | 0.004543 |
| 14 | 0.195096 | 1.8915 | 0.030816 |
| 15 | -0.092984 | -0.9015 | 0.81519 |
| 16 | -0.100128 | -0.9708 | 0.832924 |
| 17 | 0.128082 | 1.2418 | 0.108699 |
| 18 | -0.228527 | -2.2156 | 0.985435 |
| 19 | -0.015604 | -0.1513 | 0.559962 |
| 20 | -0.083883 | -0.8133 | 0.790944 |
| 21 | -0.093689 | -0.9084 | 0.816992 |
| 22 | 0.076865 | 0.7452 | 0.228994 |
| 23 | -0.12482 | -1.2102 | 0.885376 |
| 24 | -0.084243 | -0.8168 | 0.791937 |
| 25 | 0.060124 | 0.5829 | 0.28067 |
| 26 | -0.060233 | -0.584 | 0.719683 |
| 27 | -0.159536 | -1.5468 | 0.93736 |
| 28 | 0.033463 | 0.3244 | 0.373165 |
| 29 | 0.019258 | 0.1867 | 0.426145 |
| 30 | -0.170808 | -1.656 | 0.949476 |
| 31 | -0.092995 | -0.9016 | 0.815219 |
| 32 | 0.090979 | 0.8821 | 0.189993 |
| 33 | -0.185964 | -1.803 | 0.962703 |
| 34 | 0.042989 | 0.4168 | 0.338891 |
| 35 | 0.054347 | 0.5269 | 0.299746 |
| 36 | 0.069413 | 0.673 | 0.251304 |
| 37 | 0.066318 | 0.643 | 0.260901 |
| 38 | -0.04459 | -0.4323 | 0.666748 |
| 39 | 0.022715 | 0.2202 | 0.413085 |
| 40 | -0.036166 | -0.3506 | 0.63668 |
| 41 | -0.073442 | -0.712 | 0.760899 |
| 42 | 0.016838 | 0.1632 | 0.435338 |
| 43 | -0.061496 | -0.5962 | 0.723772 |
| 44 | 0.027945 | 0.2709 | 0.393519 |
| 45 | -0.050641 | -0.491 | 0.687708 |
| 46 | 0.021882 | 0.2122 | 0.416222 |
| 47 | -0.115379 | -1.1186 | 0.866928 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196359202kpbx0b27v7yj160/2tvht1196359842.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')
Copyright
This work is licensed under a
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Software written by Ed van Stee & Patrick Wessa
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