Q2 Autocorrelation
| 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 | 7.746 | 0 |
| 1 | 0.037865 | 0.2933 | 0.385153 |
| 2 | -0.255508 | -1.9792 | 0.973804 |
| 3 | 0.269674 | 2.0889 | 0.020484 |
| 4 | -0.217732 | -1.6865 | 0.951558 |
| 5 | -0.014381 | -0.1114 | 0.544161 |
| 6 | 0.565156 | 4.3777 | 2.4e-05 |
| 7 | -0.056108 | -0.4346 | 0.667299 |
| 8 | -0.223125 | -1.7283 | 0.955463 |
| 9 | 0.181798 | 1.4082 | 0.082117 |
| 10 | -0.362642 | -2.809 | 0.996651 |
| 11 | -0.06892 | -0.5339 | 0.702292 |
| 12 | 0.540288 | 4.1851 | 4.7e-05 |
| 13 | -0.141091 | -1.0929 | 0.860593 |
| 14 | -0.203485 | -1.5762 | 0.939879 |
| 15 | 0.147518 | 1.1427 | 0.128858 |
| 16 | -0.254922 | -1.9746 | 0.973541 |
| 17 | -0.061915 | -0.4796 | 0.683369 |
| 18 | 0.359821 | 2.7872 | 0.003555 |
| 19 | -0.095492 | -0.7397 | 0.768811 |
| 20 | -0.055854 | -0.4326 | 0.666589 |
| 21 | 0.098114 | 0.76 | 0.225118 |
| 22 | -0.303252 | -2.349 | 0.988932 |
| 23 | 0.065115 | 0.5044 | 0.30792 |
| 24 | 0.364935 | 2.8268 | 0.00319 |
| 25 | -0.117816 | -0.9126 | 0.817448 |
| 26 | -0.093339 | -0.723 | 0.763756 |
| 27 | 0.091345 | 0.7076 | 0.24098 |
| 28 | -0.215594 | -1.67 | 0.949934 |
| 29 | -0.025086 | -0.1943 | 0.576709 |
| 30 | 0.236588 | 1.8326 | 0.035913 |
| 31 | -0.093304 | -0.7227 | 0.763673 |
| 32 | -0.060176 | -0.4661 | 0.678591 |
| 33 | -0.066402 | -0.5143 | 0.695551 |
| 34 | -0.253006 | -1.9598 | 0.972664 |
| 35 | 0.000251 | 0.0019 | 0.499228 |
| 36 | 0.178673 | 1.384 | 0.085744 |
| 37 | -0.032004 | -0.2479 | 0.597472 |
| 38 | -0.097096 | -0.7521 | 0.772534 |
| 39 | -0.037473 | -0.2903 | 0.613693 |
| 40 | -0.165553 | -1.2824 | 0.897677 |
| 41 | -0.069779 | -0.5405 | 0.704575 |
| 42 | 0.077403 | 0.5996 | 0.275527 |
| 43 | -0.023543 | -0.1824 | 0.572043 |
| 44 | -0.043592 | -0.3377 | 0.631603 |
| 45 | -0.058207 | -0.4509 | 0.673146 |
| 46 | -0.084883 | -0.6575 | 0.743313 |
| 47 | 0.008519 | 0.066 | 0.473804 |
| 48 | 0.069598 | 0.5391 | 0.295904 |
| 49 | 0.02814 | 0.218 | 0.414095 |
| 50 | 0.004946 | 0.0383 | 0.484783 |
| 51 | 0.01026 | 0.0795 | 0.46846 |
| 52 | -0.005258 | -0.0407 | 0.516176 |
| 53 | 0.00541 | 0.0419 | 0.483357 |
| 54 | 0.021821 | 0.169 | 0.433173 |
| 55 | 0.010219 | 0.0792 | 0.468587 |
| 56 | -0.000817 | -0.0063 | 0.502513 |
| 57 | -0.012098 | -0.0937 | 0.537175 |
| 58 | -0.003908 | -0.0303 | 0.512025 |
| 59 | -9.3e-05 | -7e-04 | 0.500287 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.037865 | 0.2933 | 0.385153 |
| 1 | -0.257311 | -1.9931 | 0.974599 |
| 2 | 0.312703 | 2.4222 | 0.009232 |
| 3 | -0.396611 | -3.0721 | 0.998403 |
| 4 | 0.353936 | 2.7416 | 0.004023 |
| 5 | 0.303433 | 2.3504 | 0.01103 |
| 6 | -0.015949 | -0.1235 | 0.548954 |
| 7 | -0.094627 | -0.733 | 0.766786 |
| 8 | 0.012124 | 0.0939 | 0.462747 |
| 9 | -0.41621 | -3.2239 | 0.998977 |
| 10 | 0.240636 | 1.864 | 0.033611 |
| 11 | 0.053809 | 0.4168 | 0.339154 |
| 12 | 0.007367 | 0.0571 | 0.477343 |
| 13 | -0.07154 | -0.5541 | 0.709231 |
| 14 | 0.008544 | 0.0662 | 0.473727 |
| 15 | 0.054273 | 0.4204 | 0.337848 |
| 16 | -0.044763 | -0.3467 | 0.634997 |
| 17 | -0.090331 | -0.6997 | 0.756592 |
| 18 | 0.102185 | 0.7915 | 0.215879 |
| 19 | 0.068813 | 0.533 | 0.297992 |
| 20 | -0.146025 | -1.1311 | 0.868743 |
| 21 | 0.072182 | 0.5591 | 0.289082 |
| 22 | 0.081589 | 0.632 | 0.264899 |
| 23 | 0.059237 | 0.4588 | 0.324002 |
| 24 | -0.044729 | -0.3465 | 0.634898 |
| 25 | -0.113586 | -0.8798 | 0.808769 |
| 26 | 0.054334 | 0.4209 | 0.337677 |
| 27 | -0.037503 | -0.2905 | 0.61378 |
| 28 | -0.131139 | -1.0158 | 0.843097 |
| 29 | 0.07469 | 0.5785 | 0.282531 |
| 30 | -0.039131 | -0.3031 | 0.618571 |
| 31 | -0.079567 | -0.6163 | 0.729994 |
| 32 | -0.136131 | -1.0545 | 0.852052 |
| 33 | 0.062096 | 0.481 | 0.316135 |
| 34 | -0.172285 | -1.3345 | 0.906461 |
| 35 | 0.099383 | 0.7698 | 0.222213 |
| 36 | 0.041373 | 0.3205 | 0.374862 |
| 37 | -0.022694 | -0.1758 | 0.569475 |
| 38 | -0.061243 | -0.4744 | 0.681527 |
| 39 | -0.010168 | -0.0788 | 0.531259 |
| 40 | -0.110951 | -0.8594 | 0.803236 |
| 41 | -0.07915 | -0.6131 | 0.728934 |
| 42 | -0.239404 | -1.8544 | 0.965702 |
| 43 | 0.137571 | 1.0656 | 0.145432 |
| 44 | 0.046503 | 0.3602 | 0.359977 |
| 45 | 0.047035 | 0.3643 | 0.358447 |
| 46 | 0.06191 | 0.4796 | 0.316645 |
| 47 | -0.022103 | -0.1712 | 0.567683 |
| 48 | 0.027666 | 0.2143 | 0.415521 |
| 49 | 0.001777 | 0.0138 | 0.494532 |
| 50 | -0.036507 | -0.2828 | 0.610843 |
| 51 | 0.061152 | 0.4737 | 0.318723 |
| 52 | 0.026288 | 0.2036 | 0.419666 |
| 53 | -0.107013 | -0.8289 | 0.794782 |
| 54 | 0.00777 | 0.0602 | 0.476105 |
| 55 | 0.018134 | 0.1405 | 0.44438 |
| 56 | -0.018721 | -0.145 | 0.557406 |
| 57 | 0.019399 | 0.1503 | 0.440531 |
| 58 | -0.012446 | -0.0964 | 0.538239 |
| 59 | NA | NA | NA |
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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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