paper (vrm/ACF 2) - update 21/12
| 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 | 6.9282 | 0 |
| 1 | 0.294873 | 2.0429 | 0.023285 |
| 2 | 0.344726 | 2.3883 | 0.010453 |
| 3 | 0.168291 | 1.166 | 0.124697 |
| 4 | 0.103951 | 0.7202 | 0.237448 |
| 5 | 0.109959 | 0.7618 | 0.224948 |
| 6 | 0.048727 | 0.3376 | 0.368571 |
| 7 | -0.068715 | -0.4761 | 0.681908 |
| 8 | -0.059056 | -0.4092 | 0.657877 |
| 9 | -0.008183 | -0.0567 | 0.522487 |
| 10 | -0.242711 | -1.6815 | 0.950424 |
| 11 | -0.235773 | -1.6335 | 0.945545 |
| 12 | -0.388854 | -2.6941 | 0.995152 |
| 13 | -0.308024 | -2.1341 | 0.981013 |
| 14 | -0.169655 | -1.1754 | 0.877184 |
| 15 | -0.064416 | -0.4463 | 0.671302 |
| 16 | -0.263596 | -1.8262 | 0.962982 |
| 17 | 0.015055 | 0.1043 | 0.458681 |
| 18 | -0.055609 | -0.3853 | 0.649129 |
| 19 | -0.055044 | -0.3814 | 0.647689 |
| 20 | 0.023182 | 0.1606 | 0.436537 |
| 21 | -0.063331 | -0.4388 | 0.668602 |
| 22 | -0.000407 | -0.0028 | 0.50112 |
| 23 | 0.117322 | 0.8128 | 0.210165 |
| 24 | -0.00306 | -0.0212 | 0.508413 |
| 25 | 0.06643 | 0.4602 | 0.32371 |
| 26 | 0.066755 | 0.4625 | 0.322909 |
| 27 | -0.049011 | -0.3396 | 0.632164 |
| 28 | -0.006818 | -0.0472 | 0.51874 |
| 29 | -0.048079 | -0.3331 | 0.629747 |
| 30 | -0.061169 | -0.4238 | 0.663193 |
| 31 | 0.030765 | 0.2131 | 0.416057 |
| 32 | 0.060503 | 0.4192 | 0.338477 |
| 33 | 0.065193 | 0.4517 | 0.326769 |
| 34 | 0.031968 | 0.2215 | 0.412829 |
| 35 | 0.016152 | 0.1119 | 0.455682 |
| 36 | -0.024355 | -0.1687 | 0.566644 |
| 37 | -0.003941 | -0.0273 | 0.510835 |
| 38 | 0.041365 | 0.2866 | 0.387832 |
| 39 | -0.003635 | -0.0252 | 0.509993 |
| 40 | 0.137238 | 0.9508 | 0.173231 |
| 41 | 0.056821 | 0.3937 | 0.347784 |
| 42 | 0.042549 | 0.2948 | 0.384713 |
| 43 | 0.012373 | 0.0857 | 0.466022 |
| 44 | -0.069332 | -0.4803 | 0.683418 |
| 45 | -0.035769 | -0.2478 | 0.597334 |
| 46 | -0.05545 | -0.3842 | 0.648726 |
| 47 | -0.010209 | -0.0707 | 0.528046 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.294873 | 2.0429 | 0.023285 |
| 1 | 0.282324 | 1.956 | 0.028149 |
| 2 | 0.014387 | 0.0997 | 0.460508 |
| 3 | -0.037491 | -0.2597 | 0.601915 |
| 4 | 0.05123 | 0.3549 | 0.362099 |
| 5 | -0.00491 | -0.034 | 0.513497 |
| 6 | -0.143587 | -0.9948 | 0.837588 |
| 7 | -0.044586 | -0.3089 | 0.620634 |
| 8 | 0.088584 | 0.6137 | 0.271147 |
| 9 | -0.261518 | -1.8119 | 0.961866 |
| 10 | -0.198632 | -1.3762 | 0.91242 |
| 11 | -0.207463 | -1.4373 | 0.921447 |
| 12 | -0.072051 | -0.4992 | 0.690034 |
| 13 | 0.081656 | 0.5657 | 0.287106 |
| 14 | 0.157869 | 1.0937 | 0.139763 |
| 15 | -0.247878 | -1.7174 | 0.953819 |
| 16 | 0.126684 | 0.8777 | 0.192241 |
| 17 | 0.068588 | 0.4752 | 0.318404 |
| 18 | -0.140415 | -0.9728 | 0.83224 |
| 19 | -0.033836 | -0.2344 | 0.592172 |
| 20 | 0.00013 | 9e-04 | 0.499642 |
| 21 | -0.120663 | -0.836 | 0.796346 |
| 22 | -0.038864 | -0.2693 | 0.605558 |
| 23 | -0.18851 | -1.306 | 0.901118 |
| 24 | 0.044837 | 0.3106 | 0.378709 |
| 25 | 0.008105 | 0.0562 | 0.477727 |
| 26 | -0.104214 | -0.722 | 0.763106 |
| 27 | -0.136044 | -0.9425 | 0.824683 |
| 28 | -0.044097 | -0.3055 | 0.619352 |
| 29 | 0.035406 | 0.2453 | 0.403635 |
| 30 | 0.085516 | 0.5925 | 0.278157 |
| 31 | -0.097645 | -0.6765 | 0.749015 |
| 32 | 0.149448 | 1.0354 | 0.152833 |
| 33 | -0.091942 | -0.637 | 0.736422 |
| 34 | -0.144327 | -0.9999 | 0.83882 |
| 35 | -0.047023 | -0.3258 | 0.626999 |
| 36 | -0.06653 | -0.4609 | 0.676537 |
| 37 | 0.039346 | 0.2726 | 0.393167 |
| 38 | -0.015117 | -0.1047 | 0.541488 |
| 39 | -0.110735 | -0.7672 | 0.776639 |
| 40 | 0.040307 | 0.2793 | 0.390623 |
| 41 | -0.020725 | -0.1436 | 0.556785 |
| 42 | -0.059245 | -0.4105 | 0.658353 |
| 43 | -0.059349 | -0.4112 | 0.658614 |
| 44 | 0.019764 | 0.1369 | 0.445829 |
| 45 | -0.07195 | -0.4985 | 0.68979 |
| 46 | -0.000846 | -0.0059 | 0.502328 |
| 47 | NA | NA | NA |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198245378goxyn5pf3ikyl4z/1d3i21198246422.png (open in new window) |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198245378goxyn5pf3ikyl4z/2wybu1198246422.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/21/t1198245378goxyn5pf3ikyl4z/2wybu1198246422.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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