PACF Steenkolen D=1 en d=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 | 6.8557 | 0 |
| 1 | 0.563094 | 3.8604 | 0.000172 |
| 2 | 0.414057 | 2.8386 | 0.003336 |
| 3 | 0.23123 | 1.5852 | 0.05981 |
| 4 | 0.115477 | 0.7917 | 0.216264 |
| 5 | 0.014304 | 0.0981 | 0.46115 |
| 6 | 0.091135 | 0.6248 | 0.267566 |
| 7 | -0.064308 | -0.4409 | 0.669338 |
| 8 | -0.117172 | -0.8033 | 0.787075 |
| 9 | -0.127442 | -0.8737 | 0.806638 |
| 10 | -0.102839 | -0.705 | 0.757864 |
| 11 | -0.23798 | -1.6315 | 0.945267 |
| 12 | -0.360485 | -2.4714 | 0.99143 |
| 13 | -0.364636 | -2.4998 | 0.992013 |
| 14 | -0.260047 | -1.7828 | 0.95946 |
| 15 | -0.193234 | -1.3247 | 0.90417 |
| 16 | -0.007852 | -0.0538 | 0.521351 |
| 17 | -0.064967 | -0.4454 | 0.67096 |
| 18 | -0.060962 | -0.4179 | 0.661051 |
| 19 | 0.014692 | 0.1007 | 0.4601 |
| 20 | 0.031132 | 0.2134 | 0.415957 |
| 21 | 0.054975 | 0.3769 | 0.353975 |
| 22 | 0.084789 | 0.5813 | 0.281913 |
| 23 | 0.064806 | 0.4443 | 0.329438 |
| 24 | 0.011055 | 0.0758 | 0.469955 |
| 25 | 0.088607 | 0.6075 | 0.273235 |
| 26 | 0.003473 | 0.0238 | 0.490551 |
| 27 | -0.08104 | -0.5556 | 0.709435 |
| 28 | -0.085021 | -0.5829 | 0.718618 |
| 29 | -0.058658 | -0.4021 | 0.655296 |
| 30 | -0.063632 | -0.4362 | 0.66767 |
| 31 | -0.059341 | -0.4068 | 0.657008 |
| 32 | -0.063304 | -0.434 | 0.666858 |
| 33 | -0.10511 | -0.7206 | 0.762636 |
| 34 | -0.182707 | -1.2526 | 0.891722 |
| 35 | -0.076379 | -0.5236 | 0.698502 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.563094 | 3.8604 | 0.000172 |
| 1 | 0.14201 | 0.9736 | 0.167627 |
| 2 | -0.072894 | -0.4997 | 0.690205 |
| 3 | -0.046524 | -0.319 | 0.624412 |
| 4 | -0.057673 | -0.3954 | 0.652826 |
| 5 | 0.169479 | 1.1619 | 0.125573 |
| 6 | -0.209171 | -1.434 | 0.920905 |
| 7 | -0.100977 | -0.6923 | 0.753911 |
| 8 | 0.027234 | 0.1867 | 0.426347 |
| 9 | 0.038541 | 0.2642 | 0.396381 |
| 10 | -0.238683 | -1.6363 | 0.945775 |
| 11 | -0.336126 | -2.3044 | 0.987166 |
| 12 | 0.038873 | 0.2665 | 0.39551 |
| 13 | 0.221081 | 1.5157 | 0.068152 |
| 14 | -0.05185 | -0.3555 | 0.638084 |
| 15 | 0.003341 | 0.0229 | 0.490913 |
| 16 | -0.143813 | -0.9859 | 0.835393 |
| 17 | 0.089783 | 0.6155 | 0.270591 |
| 18 | 0.124799 | 0.8556 | 0.198285 |
| 19 | -0.194572 | -1.3339 | 0.90567 |
| 20 | 0.006679 | 0.0458 | 0.481837 |
| 21 | 0.075205 | 0.5156 | 0.304283 |
| 22 | 0.056749 | 0.389 | 0.349499 |
| 23 | -0.299329 | -2.0521 | 0.977123 |
| 24 | -0.063823 | -0.4375 | 0.66814 |
| 25 | 0.029146 | 0.1998 | 0.421243 |
| 26 | -0.051571 | -0.3536 | 0.637373 |
| 27 | 0.010572 | 0.0725 | 0.471265 |
| 28 | -0.049346 | -0.3383 | 0.631678 |
| 29 | 0.02636 | 0.1807 | 0.428684 |
| 30 | -0.061782 | -0.4236 | 0.663089 |
| 31 | -0.110834 | -0.7598 | 0.774428 |
| 32 | 0.030281 | 0.2076 | 0.418221 |
| 33 | -0.149805 | -1.027 | 0.845164 |
| 34 | 0.064831 | 0.4445 | 0.329376 |
| 35 | 0.03639 | 0.2495 | 0.402038 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/28/t1196260556lwy7rdv9f03d5zy/2f00t1196261045.ps (open in new window) |
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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