Workshop 5 ACF PACF Belgische uitvoer
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 2 seconds |
| R Server | 'Gwilym Jenkins' @ 72.249.127.135 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 7 | 0 |
| 1 | -0.070736 | -0.4951 | 0.688646 |
| 2 | 0.051801 | 0.3626 | 0.359228 |
| 3 | 0.326697 | 2.2869 | 0.013281 |
| 4 | -0.015076 | -0.1055 | 0.541807 |
| 5 | -0.023598 | -0.1652 | 0.565262 |
| 6 | 0.079747 | 0.5582 | 0.289614 |
| 7 | -0.278331 | -1.9483 | 0.971442 |
| 8 | 0.016073 | 0.1125 | 0.455438 |
| 9 | -0.037029 | -0.2592 | 0.601719 |
| 10 | -0.159966 | -1.1198 | 0.865863 |
| 11 | -0.096602 | -0.6762 | 0.748958 |
| 12 | -0.184461 | -1.2912 | 0.898659 |
| 13 | -0.069075 | -0.4835 | 0.684562 |
| 14 | 0.067823 | 0.4748 | 0.318534 |
| 15 | -0.097542 | -0.6828 | 0.751025 |
| 16 | -0.168631 | -1.1804 | 0.878233 |
| 17 | 0.176617 | 1.2363 | 0.111117 |
| 18 | 0.052123 | 0.3649 | 0.358394 |
| 19 | -0.054087 | -0.3786 | 0.646693 |
| 20 | 0.028669 | 0.2007 | 0.420889 |
| 21 | 0.122589 | 0.8581 | 0.197501 |
| 22 | -0.199351 | -1.3955 | 0.915415 |
| 23 | 0.159718 | 1.118 | 0.134503 |
| 24 | -0.085576 | -0.599 | 0.724044 |
| 25 | -0.200949 | -1.4066 | 0.917077 |
| 26 | 0.042679 | 0.2988 | 0.383196 |
| 27 | -0.041424 | -0.29 | 0.613468 |
| 28 | -0.107508 | -0.7526 | 0.772341 |
| 29 | 0.048897 | 0.3423 | 0.366803 |
| 30 | -0.108177 | -0.7572 | 0.773734 |
| 31 | 0.109806 | 0.7686 | 0.222896 |
| 32 | 0.053804 | 0.3766 | 0.354039 |
| 33 | -0.115912 | -0.8114 | 0.789466 |
| 34 | 0.154573 | 1.082 | 0.142272 |
| 35 | 0.090184 | 0.6313 | 0.265394 |
| 36 | -0.030907 | -0.2163 | 0.585192 |
| 37 | 0.13922 | 0.9745 | 0.167287 |
| 38 | 0.106319 | 0.7442 | 0.230146 |
| 39 | -0.008558 | -0.0599 | 0.523764 |
| 40 | 0.082841 | 0.5799 | 0.282324 |
| 41 | 0.012218 | 0.0855 | 0.466094 |
| 42 | -0.062895 | -0.4403 | 0.66916 |
| 43 | -0.034577 | -0.242 | 0.595121 |
| 44 | -0.038383 | -0.2687 | 0.605349 |
| 45 | -0.084289 | -0.59 | 0.721056 |
| 46 | -0.046944 | -0.3286 | 0.628075 |
| 47 | -0.005879 | -0.0411 | 0.516328 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.070736 | -0.4951 | 0.688646 |
| 1 | 0.047033 | 0.3292 | 0.371691 |
| 2 | 0.335937 | 2.3516 | 0.01138 |
| 3 | 0.03663 | 0.2564 | 0.399355 |
| 4 | -0.070417 | -0.4929 | 0.687864 |
| 5 | -0.045582 | -0.3191 | 0.624486 |
| 6 | -0.313202 | -2.1924 | 0.983435 |
| 7 | -0.015885 | -0.1112 | 0.544043 |
| 8 | -0.004172 | -0.0292 | 0.511591 |
| 9 | 0.034108 | 0.2388 | 0.406145 |
| 10 | -0.091297 | -0.6391 | 0.737127 |
| 11 | -0.250396 | -1.7528 | 0.957052 |
| 12 | -0.060468 | -0.4233 | 0.663026 |
| 13 | 0.10977 | 0.7684 | 0.222972 |
| 14 | 0.115206 | 0.8064 | 0.211943 |
| 15 | -0.196697 | -1.3769 | 0.912595 |
| 16 | 0.018054 | 0.1264 | 0.449974 |
| 17 | 0.062855 | 0.44 | 0.330941 |
| 18 | -0.030078 | -0.2105 | 0.582943 |
| 19 | -0.088723 | -0.6211 | 0.731281 |
| 20 | 0.097308 | 0.6812 | 0.249489 |
| 21 | -0.271394 | -1.8998 | 0.968321 |
| 22 | -0.018769 | -0.1314 | 0.551993 |
| 23 | -0.091221 | -0.6385 | 0.736955 |
| 24 | -0.095255 | -0.6668 | 0.74598 |
| 25 | -0.032985 | -0.2309 | 0.590822 |
| 26 | -0.090371 | -0.6326 | 0.735031 |
| 27 | 0.007825 | 0.0548 | 0.478271 |
| 28 | -0.007679 | -0.0538 | 0.521325 |
| 29 | 0.002819 | 0.0197 | 0.492168 |
| 30 | 0.038806 | 0.2716 | 0.393519 |
| 31 | -0.080626 | -0.5644 | 0.712466 |
| 32 | -0.093543 | -0.6548 | 0.742172 |
| 33 | 0.004221 | 0.0295 | 0.488275 |
| 34 | 0.050391 | 0.3527 | 0.3629 |
| 35 | 0.000538 | 0.0038 | 0.498505 |
| 36 | -0.041426 | -0.29 | 0.613474 |
| 37 | 0.015483 | 0.1084 | 0.457069 |
| 38 | 0.064185 | 0.4493 | 0.327599 |
| 39 | -0.069789 | -0.4885 | 0.68632 |
| 40 | -0.04108 | -0.2876 | 0.612551 |
| 41 | -0.08824 | -0.6177 | 0.730177 |
| 42 | 0.014798 | 0.1036 | 0.45896 |
| 43 | -0.109985 | -0.7699 | 0.777472 |
| 44 | 0.001875 | 0.0131 | 0.49479 |
| 45 | 0.019918 | 0.1394 | 0.444843 |
| 46 | 0.053911 | 0.3774 | 0.353761 |
| 47 | 0.044879 | 0.3142 | 0.37737 |
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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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