Autocorrelatie d=0; D=1
| 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 | 6.9282 | 0 |
| 1 | 0.322334 | 2.2332 | 0.015117 |
| 2 | 0.260994 | 1.8082 | 0.03842 |
| 3 | 0.200956 | 1.3923 | 0.08513 |
| 4 | 0.02546 | 0.1764 | 0.430364 |
| 5 | 0.058375 | 0.4044 | 0.343845 |
| 6 | -0.062043 | -0.4298 | 0.665385 |
| 7 | -0.039967 | -0.2769 | 0.608476 |
| 8 | -0.009698 | -0.0672 | 0.526646 |
| 9 | -0.190406 | -1.3192 | 0.903314 |
| 10 | -0.124184 | -0.8604 | 0.803069 |
| 11 | -0.119167 | -0.8256 | 0.793445 |
| 12 | -0.310634 | -2.1521 | 0.981778 |
| 13 | -0.159154 | -1.1027 | 0.862162 |
| 14 | -0.221072 | -1.5316 | 0.933911 |
| 15 | -0.228875 | -1.5857 | 0.940312 |
| 16 | -0.324337 | -2.2471 | 0.985365 |
| 17 | -0.161959 | -1.1221 | 0.866296 |
| 18 | -0.058305 | -0.4039 | 0.655978 |
| 19 | -0.093001 | -0.6443 | 0.738786 |
| 20 | -0.035095 | -0.2431 | 0.595535 |
| 21 | 0.089315 | 0.6188 | 0.269489 |
| 22 | 0.015111 | 0.1047 | 0.458527 |
| 23 | 0.088124 | 0.6105 | 0.272192 |
| 24 | -0.002054 | -0.0142 | 0.505649 |
| 25 | 0.149226 | 1.0339 | 0.153189 |
| 26 | 0.12489 | 0.8653 | 0.1956 |
| 27 | -0.006862 | -0.0475 | 0.51886 |
| 28 | 0.208422 | 1.444 | 0.077618 |
| 29 | 0.133749 | 0.9266 | 0.179374 |
| 30 | 0.113169 | 0.7841 | 0.218429 |
| 31 | 0.139908 | 0.9693 | 0.168625 |
| 32 | 0.102794 | 0.7122 | 0.239901 |
| 33 | -0.002702 | -0.0187 | 0.507429 |
| 34 | -0.060789 | -0.4212 | 0.662241 |
| 35 | -0.142221 | -0.9853 | 0.8353 |
| 36 | -0.116598 | -0.8078 | 0.788409 |
| 37 | -0.087041 | -0.603 | 0.725338 |
| 38 | -0.037245 | -0.258 | 0.60126 |
| 39 | 0.087248 | 0.6045 | 0.274188 |
| 40 | -0.017328 | -0.1201 | 0.54753 |
| 41 | -0.045752 | -0.317 | 0.623682 |
| 42 | 0.03901 | 0.2703 | 0.394057 |
| 43 | 0.01844 | 0.1278 | 0.449438 |
| 44 | -0.016294 | -0.1129 | 0.544706 |
| 45 | -0.013519 | -0.0937 | 0.537116 |
| 46 | 0.005865 | 0.0406 | 0.483879 |
| 47 | 0.002912 | 0.0202 | 0.491993 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.322334 | 2.2332 | 0.015117 |
| 1 | 0.17531 | 1.2146 | 0.115234 |
| 2 | 0.086429 | 0.5988 | 0.276061 |
| 3 | -0.107337 | -0.7437 | 0.769644 |
| 4 | 0.026846 | 0.186 | 0.426616 |
| 5 | -0.096634 | -0.6695 | 0.746809 |
| 6 | 0.002024 | 0.014 | 0.494435 |
| 7 | 0.024074 | 0.1668 | 0.434119 |
| 8 | -0.185276 | -1.2836 | 0.897283 |
| 9 | -0.04527 | -0.3136 | 0.622422 |
| 10 | -0.011382 | -0.0789 | 0.531262 |
| 11 | -0.246142 | -1.7053 | 0.9527 |
| 12 | -0.003123 | -0.0216 | 0.508587 |
| 13 | -0.080749 | -0.5594 | 0.710771 |
| 14 | -0.125015 | -0.8661 | 0.804636 |
| 15 | -0.285555 | -1.9784 | 0.97318 |
| 16 | 0.083018 | 0.5752 | 0.283934 |
| 17 | 0.005155 | 0.0357 | 0.485829 |
| 18 | -0.089833 | -0.6224 | 0.731682 |
| 19 | -0.045691 | -0.3166 | 0.623523 |
| 20 | 0.053034 | 0.3674 | 0.357457 |
| 21 | -0.128856 | -0.8927 | 0.811775 |
| 22 | 0.039391 | 0.2729 | 0.393047 |
| 23 | -0.177272 | -1.2282 | 0.887316 |
| 24 | 0.080384 | 0.5569 | 0.290087 |
| 25 | -0.055917 | -0.3874 | 0.649916 |
| 26 | -0.140478 | -0.9733 | 0.832349 |
| 27 | 0.011688 | 0.081 | 0.467899 |
| 28 | 0.07178 | 0.4973 | 0.310621 |
| 29 | -0.045882 | -0.3179 | 0.624023 |
| 30 | -0.060562 | -0.4196 | 0.66167 |
| 31 | -0.001482 | -0.0103 | 0.504075 |
| 32 | -0.118451 | -0.8207 | 0.792049 |
| 33 | -0.136604 | -0.9464 | 0.825662 |
| 34 | -0.108075 | -0.7488 | 0.771174 |
| 35 | -0.204191 | -1.4147 | 0.918191 |
| 36 | 0.111033 | 0.7693 | 0.222754 |
| 37 | -0.000707 | -0.0049 | 0.501945 |
| 38 | 0.043575 | 0.3019 | 0.382018 |
| 39 | -0.109812 | -0.7608 | 0.77475 |
| 40 | 0.020224 | 0.1401 | 0.444577 |
| 41 | 0.00606 | 0.042 | 0.483343 |
| 42 | -0.02262 | -0.1567 | 0.561937 |
| 43 | -0.012466 | -0.0864 | 0.534233 |
| 44 | -0.009563 | -0.0663 | 0.526276 |
| 45 | -0.074782 | -0.5181 | 0.696618 |
| 46 | -0.019127 | -0.1325 | 0.552435 |
| 47 | NA | NA | NA |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/27/t1196158634vpm2x5pyd9dc031/2pi6h1196159102.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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