paper diesel (vrm/acf 2 lambda=1)
| 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 | 7.6811 | 0 |
| 1 | 0.202949 | 1.5589 | 0.062186 |
| 2 | -0.116978 | -0.8985 | 0.81372 |
| 3 | -0.112941 | -0.8675 | 0.805412 |
| 4 | -0.049118 | -0.3773 | 0.646341 |
| 5 | 0.039657 | 0.3046 | 0.380866 |
| 6 | 0.063291 | 0.4861 | 0.314332 |
| 7 | -0.055607 | -0.4271 | 0.664577 |
| 8 | -0.130952 | -1.0059 | 0.840704 |
| 9 | -0.123469 | -0.9484 | 0.826598 |
| 10 | 0.136319 | 1.0471 | 0.149666 |
| 11 | 0.252039 | 1.9359 | 0.028835 |
| 12 | -0.013001 | -0.0999 | 0.539605 |
| 13 | 0.04339 | 0.3333 | 0.370051 |
| 14 | -0.008456 | -0.065 | 0.525785 |
| 15 | -0.086168 | -0.6619 | 0.744684 |
| 16 | -0.171311 | -1.3159 | 0.903346 |
| 17 | 0.016442 | 0.1263 | 0.449963 |
| 18 | 0.084168 | 0.6465 | 0.260229 |
| 19 | 0.052375 | 0.4023 | 0.344458 |
| 20 | 0.020209 | 0.1552 | 0.438587 |
| 21 | -0.013868 | -0.1065 | 0.542234 |
| 22 | -0.074059 | -0.5689 | 0.714194 |
| 23 | -0.173443 | -1.3322 | 0.906048 |
| 24 | 0.072104 | 0.5538 | 0.29089 |
| 25 | 0.049196 | 0.3779 | 0.353438 |
| 26 | -0.108894 | -0.8364 | 0.796857 |
| 27 | -0.142223 | -1.0924 | 0.860459 |
| 28 | -0.046183 | -0.3547 | 0.637974 |
| 29 | -0.019103 | -0.1467 | 0.558079 |
| 30 | 0.137263 | 1.0543 | 0.148013 |
| 31 | 0.115351 | 0.886 | 0.189599 |
| 32 | -0.028664 | -0.2202 | 0.586752 |
| 33 | -0.152627 | -1.1723 | 0.877115 |
| 34 | -0.117202 | -0.9002 | 0.814176 |
| 35 | 0.065652 | 0.5043 | 0.307969 |
| 36 | 0.034399 | 0.2642 | 0.396263 |
| 37 | -0.008645 | -0.0664 | 0.526359 |
| 38 | -0.078634 | -0.604 | 0.725921 |
| 39 | 0.014666 | 0.1127 | 0.455343 |
| 40 | -0.051794 | -0.3978 | 0.653907 |
| 41 | 0.002148 | 0.0165 | 0.493447 |
| 42 | 0.03313 | 0.2545 | 0.400007 |
| 43 | -0.09021 | -0.6929 | 0.754459 |
| 44 | -0.133711 | -1.0271 | 0.845706 |
| 45 | -0.000761 | -0.0058 | 0.502321 |
| 46 | 0.035577 | 0.2733 | 0.392798 |
| 47 | -0.015812 | -0.1215 | 0.548128 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.202949 | 1.5589 | 0.062186 |
| 1 | -0.164961 | -1.2671 | 0.894948 |
| 2 | -0.055542 | -0.4266 | 0.664398 |
| 3 | -0.032198 | -0.2473 | 0.597238 |
| 4 | 0.036523 | 0.2805 | 0.390022 |
| 5 | 0.03207 | 0.2463 | 0.40314 |
| 6 | -0.078663 | -0.6042 | 0.725994 |
| 7 | -0.092429 | -0.71 | 0.759737 |
| 8 | -0.089429 | -0.6869 | 0.752588 |
| 9 | 0.16113 | 1.2377 | 0.110372 |
| 10 | 0.158447 | 1.2171 | 0.114215 |
| 11 | -0.099576 | -0.7649 | 0.776297 |
| 12 | 0.151048 | 1.1602 | 0.125317 |
| 13 | -0.015765 | -0.1211 | 0.547985 |
| 14 | -0.073335 | -0.5633 | 0.712317 |
| 15 | -0.204173 | -1.5683 | 0.938918 |
| 16 | 0.077125 | 0.5924 | 0.277921 |
| 17 | 0.077117 | 0.5923 | 0.27794 |
| 18 | 0.058685 | 0.4508 | 0.326904 |
| 19 | 0.042234 | 0.3244 | 0.37339 |
| 20 | -0.054759 | -0.4206 | 0.662217 |
| 21 | -0.059448 | -0.4566 | 0.675193 |
| 22 | -0.234994 | -1.805 | 0.961913 |
| 23 | 0.053961 | 0.4145 | 0.340011 |
| 24 | -0.018265 | -0.1403 | 0.555547 |
| 25 | -0.026329 | -0.2022 | 0.579787 |
| 26 | -0.010019 | -0.077 | 0.530541 |
| 27 | -0.056148 | -0.4313 | 0.666083 |
| 28 | -0.037918 | -0.2913 | 0.614062 |
| 29 | 0.041059 | 0.3154 | 0.376793 |
| 30 | 0.003723 | 0.0286 | 0.48864 |
| 31 | -0.077455 | -0.5949 | 0.722921 |
| 32 | -0.017301 | -0.1329 | 0.552635 |
| 33 | 0.003868 | 0.0297 | 0.488199 |
| 34 | 0.002178 | 0.0167 | 0.493354 |
| 35 | 0.007026 | 0.054 | 0.478571 |
| 36 | -0.002266 | -0.0174 | 0.506915 |
| 37 | -0.072776 | -0.559 | 0.710863 |
| 38 | 0.061821 | 0.4749 | 0.318321 |
| 39 | -0.067761 | -0.5205 | 0.697661 |
| 40 | -0.055068 | -0.423 | 0.663078 |
| 41 | -0.012122 | -0.0931 | 0.536933 |
| 42 | -0.121604 | -0.9341 | 0.82296 |
| 43 | -0.084652 | -0.6502 | 0.740964 |
| 44 | 0.026493 | 0.2035 | 0.419724 |
| 45 | 0.029074 | 0.2233 | 0.412029 |
| 46 | -0.016971 | -0.1304 | 0.551636 |
| 47 | 0.024192 | 0.1858 | 0.42661 |
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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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