paper tijdreeks 2: autocorrelation 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 | 7.746 | 0 |
| 1 | 0.580322 | 4.4952 | 1.6e-05 |
| 2 | 0.425311 | 3.2944 | 0.000829 |
| 3 | 0.569355 | 4.4102 | 2.2e-05 |
| 4 | 0.346197 | 2.6816 | 0.004724 |
| 5 | 0.4184 | 3.2409 | 0.000973 |
| 6 | 0.557078 | 4.3151 | 3e-05 |
| 7 | 0.317969 | 2.463 | 0.008333 |
| 8 | 0.346676 | 2.6853 | 0.004678 |
| 9 | 0.375389 | 2.9078 | 0.002548 |
| 10 | 0.129371 | 1.0021 | 0.160159 |
| 11 | 0.261998 | 2.0294 | 0.023429 |
| 12 | 0.438482 | 3.3965 | 0.000608 |
| 13 | 0.146739 | 1.1366 | 0.130105 |
| 14 | 0.083945 | 0.6502 | 0.259012 |
| 15 | 0.107747 | 0.8346 | 0.203626 |
| 16 | -0.05395 | -0.4179 | 0.661243 |
| 17 | 0.065621 | 0.5083 | 0.306553 |
| 18 | 0.115646 | 0.8958 | 0.186973 |
| 19 | -0.078316 | -0.6066 | 0.726808 |
| 20 | 0.013593 | 0.1053 | 0.458249 |
| 21 | -0.008816 | -0.0683 | 0.527108 |
| 22 | -0.182437 | -1.4131 | 0.918611 |
| 23 | -0.051087 | -0.3957 | 0.653143 |
| 24 | 0.001134 | 0.0088 | 0.496509 |
| 25 | -0.132086 | -1.0231 | 0.844825 |
| 26 | -0.166143 | -1.2869 | 0.89847 |
| 27 | -0.225267 | -1.7449 | 0.95694 |
| 28 | -0.272958 | -2.1143 | 0.980674 |
| 29 | -0.178653 | -1.3838 | 0.914233 |
| 30 | -0.169813 | -1.3154 | 0.903304 |
| 31 | -0.225979 | -1.7504 | 0.957422 |
| 32 | -0.186776 | -1.4468 | 0.923416 |
| 33 | -0.192692 | -1.4926 | 0.929607 |
| 34 | -0.260286 | -2.0162 | 0.975867 |
| 35 | -0.195984 | -1.5181 | 0.932877 |
| 36 | -0.148786 | -1.1525 | 0.873155 |
| 37 | -0.209676 | -1.6241 | 0.945206 |
| 38 | -0.256749 | -1.9888 | 0.974354 |
| 39 | -0.276861 | -2.1446 | 0.981976 |
| 40 | -0.310556 | -2.4056 | 0.990376 |
| 41 | -0.234206 | -1.8142 | 0.962673 |
| 42 | -0.185606 | -1.4377 | 0.922142 |
| 43 | -0.195403 | -1.5136 | 0.93231 |
| 44 | -0.188144 | -1.4574 | 0.924884 |
| 45 | -0.184665 | -1.4304 | 0.921106 |
| 46 | -0.203669 | -1.5776 | 0.940043 |
| 47 | -0.176812 | -1.3696 | 0.912039 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.580322 | 4.4952 | 1.6e-05 |
| 1 | 0.133495 | 1.034 | 0.152631 |
| 2 | 0.426793 | 3.3059 | 0.000801 |
| 3 | -0.226826 | -1.757 | 0.957989 |
| 4 | 0.384459 | 2.978 | 0.002091 |
| 5 | 0.088209 | 0.6833 | 0.248535 |
| 6 | -0.095019 | -0.736 | 0.767706 |
| 7 | 0.069827 | 0.5409 | 0.295297 |
| 8 | -0.096899 | -0.7506 | 0.77208 |
| 9 | -0.166985 | -1.2935 | 0.899595 |
| 10 | 0.146858 | 1.1376 | 0.129915 |
| 11 | 0.251389 | 1.9473 | 0.028095 |
| 12 | -0.332071 | -2.5722 | 0.993701 |
| 13 | -0.207316 | -1.6059 | 0.943222 |
| 14 | -0.084447 | -0.6541 | 0.742234 |
| 15 | 0.078568 | 0.6086 | 0.272549 |
| 16 | -0.001978 | -0.0153 | 0.506086 |
| 17 | -0.034384 | -0.2663 | 0.604555 |
| 18 | -0.057783 | -0.4476 | 0.671968 |
| 19 | 0.050623 | 0.3921 | 0.348179 |
| 20 | 0.001015 | 0.0079 | 0.496878 |
| 21 | 0.075155 | 0.5821 | 0.281324 |
| 22 | -0.082831 | -0.6416 | 0.738215 |
| 23 | -0.056048 | -0.4341 | 0.667129 |
| 24 | 0.044827 | 0.3472 | 0.364816 |
| 25 | -0.185867 | -1.4397 | 0.922428 |
| 26 | -0.020904 | -0.1619 | 0.564046 |
| 27 | -0.034553 | -0.2676 | 0.605056 |
| 28 | -0.044209 | -0.3424 | 0.633393 |
| 29 | -0.010285 | -0.0797 | 0.531617 |
| 30 | 0.089832 | 0.6958 | 0.244609 |
| 31 | -0.052966 | -0.4103 | 0.658466 |
| 32 | 0.070914 | 0.5493 | 0.292421 |
| 33 | -0.010764 | -0.0834 | 0.533085 |
| 34 | 0.055125 | 0.427 | 0.335455 |
| 35 | -0.045599 | -0.3532 | 0.637416 |
| 36 | -0.100595 | -0.7792 | 0.780538 |
| 37 | -0.080683 | -0.625 | 0.732818 |
| 38 | 0.003434 | 0.0266 | 0.489435 |
| 39 | -0.141031 | -1.0924 | 0.860493 |
| 40 | 0.04657 | 0.3607 | 0.359784 |
| 41 | -0.032131 | -0.2489 | 0.59785 |
| 42 | 0.091315 | 0.7073 | 0.241052 |
| 43 | -0.030606 | -0.2371 | 0.593295 |
| 44 | -0.003366 | -0.0261 | 0.510357 |
| 45 | 0.070911 | 0.5493 | 0.292428 |
| 46 | -0.015917 | -0.1233 | 0.548857 |
| 47 | 0.011495 | 0.089 | 0.464674 |
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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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