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 | 9 | 0 |
| 1 | 0.621438 | 5.5929 | 0 |
| 2 | 0.500255 | 4.5023 | 1.1e-05 |
| 3 | 0.561272 | 5.0514 | 1e-06 |
| 4 | 0.503679 | 4.5331 | 1e-05 |
| 5 | 0.501408 | 4.5127 | 1.1e-05 |
| 6 | 0.420254 | 3.7823 | 0.000148 |
| 7 | 0.433298 | 3.8997 | 9.9e-05 |
| 8 | 0.398111 | 3.583 | 0.000289 |
| 9 | 0.29732 | 2.6759 | 0.004509 |
| 10 | 0.292528 | 2.6327 | 0.00507 |
| 11 | 0.369258 | 3.3233 | 0.000669 |
| 12 | 0.482396 | 4.3416 | 2e-05 |
| 13 | 0.258633 | 2.3277 | 0.011212 |
| 14 | 0.16497 | 1.4847 | 0.070748 |
| 15 | 0.17231 | 1.5508 | 0.062425 |
| 16 | 0.163115 | 1.468 | 0.072984 |
| 17 | 0.166969 | 1.5027 | 0.0684 |
| 18 | 0.056498 | 0.5085 | 0.30625 |
| 19 | 0.112786 | 1.0151 | 0.156547 |
| 20 | 0.072825 | 0.6554 | 0.257027 |
| 21 | -0.009674 | -0.0871 | 0.534581 |
| 22 | 0.020106 | 0.181 | 0.428429 |
| 23 | 0.066883 | 0.6019 | 0.274445 |
| 24 | 0.120996 | 1.089 | 0.1397 |
| 25 | -0.017434 | -0.1569 | 0.562144 |
| 26 | -0.053531 | -0.4818 | 0.684368 |
| 27 | -0.038287 | -0.3446 | 0.634351 |
| 28 | -0.06483 | -0.5835 | 0.7194 |
| 29 | -0.023652 | -0.2129 | 0.584017 |
| 30 | -0.111187 | -1.0007 | 0.840019 |
| 31 | -0.103321 | -0.9299 | 0.822405 |
| 32 | -0.096807 | -0.8713 | 0.806907 |
| 33 | -0.101308 | -0.9118 | 0.817702 |
| 34 | -0.106653 | -0.9599 | 0.830012 |
| 35 | -0.076908 | -0.6922 | 0.754595 |
| 36 | 0.023761 | 0.2138 | 0.415602 |
| 37 | -0.117674 | -1.0591 | 0.85364 |
| 38 | -0.191706 | -1.7254 | 0.955862 |
| 39 | -0.150557 | -1.355 | 0.91041 |
| 40 | -0.179665 | -1.617 | 0.945115 |
| 41 | -0.176302 | -1.5867 | 0.941764 |
| 42 | -0.248966 | -2.2407 | 0.986108 |
| 43 | -0.25856 | -2.327 | 0.98877 |
| 44 | -0.274346 | -2.4691 | 0.992176 |
| 45 | -0.292743 | -2.6347 | 0.994956 |
| 46 | -0.280261 | -2.5223 | 0.993192 |
| 47 | -0.252065 | -2.2686 | 0.987023 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.621438 | 5.5929 | 0 |
| 1 | 0.185837 | 1.6725 | 0.049139 |
| 2 | 0.325135 | 2.9262 | 0.002225 |
| 3 | 0.077159 | 0.6944 | 0.244701 |
| 4 | 0.161702 | 1.4553 | 0.074723 |
| 5 | -0.072164 | -0.6495 | 0.741065 |
| 6 | 0.117956 | 1.0616 | 0.145785 |
| 7 | -0.055024 | -0.4952 | 0.689106 |
| 8 | -0.085591 | -0.7703 | 0.778324 |
| 9 | -0.032261 | -0.2903 | 0.613853 |
| 10 | 0.183811 | 1.6543 | 0.050968 |
| 11 | 0.315857 | 2.8427 | 0.002829 |
| 12 | -0.302559 | -2.723 | 0.99604 |
| 13 | -0.16982 | -1.5284 | 0.934843 |
| 14 | -0.23829 | -2.1446 | 0.98251 |
| 15 | 0.084821 | 0.7634 | 0.223724 |
| 16 | 0.036101 | 0.3249 | 0.373044 |
| 17 | -0.089364 | -0.8043 | 0.788204 |
| 18 | 0.076758 | 0.6908 | 0.245826 |
| 19 | -0.029296 | -0.2637 | 0.603647 |
| 20 | 0.102064 | 0.9186 | 0.180523 |
| 21 | -0.075778 | -0.682 | 0.751407 |
| 22 | 0.003298 | 0.0297 | 0.488198 |
| 23 | -0.036372 | -0.3273 | 0.627876 |
| 24 | -0.000272 | -0.0024 | 0.500972 |
| 25 | 0.072045 | 0.6484 | 0.259277 |
| 26 | -0.070989 | -0.6389 | 0.737655 |
| 27 | -0.058911 | -0.5302 | 0.701287 |
| 28 | 0.020752 | 0.1868 | 0.426156 |
| 29 | -0.020033 | -0.1803 | 0.571317 |
| 30 | -0.092748 | -0.8347 | 0.796837 |
| 31 | 0.010157 | 0.0914 | 0.463694 |
| 32 | 0.146824 | 1.3214 | 0.095042 |
| 33 | -0.051173 | -0.4606 | 0.676824 |
| 34 | 0.023333 | 0.21 | 0.417099 |
| 35 | 0.081005 | 0.729 | 0.234038 |
| 36 | -0.124312 | -1.1188 | 0.866735 |
| 37 | -0.187217 | -1.685 | 0.952076 |
| 38 | -0.093967 | -0.8457 | 0.799895 |
| 39 | -0.039832 | -0.3585 | 0.639546 |
| 40 | -0.045676 | -0.4111 | 0.658952 |
| 41 | 0.03087 | 0.2778 | 0.390927 |
| 42 | -0.046217 | -0.416 | 0.660729 |
| 43 | -0.099685 | -0.8972 | 0.813856 |
| 44 | -0.044019 | -0.3962 | 0.653491 |
| 45 | -0.009041 | -0.0814 | 0.532327 |
| 46 | 0.026932 | 0.2424 | 0.404547 |
| 47 | 0.080803 | 0.7272 | 0.234592 |
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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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