autocorrelatie: export D=1 en d=0
| 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 | 6.9282 | 0 |
| 1 | 0.379818 | 2.6315 | 0.005699 |
| 2 | 0.395163 | 2.7378 | 0.004326 |
| 3 | 0.19011 | 1.3171 | 0.097026 |
| 4 | 0.283599 | 1.9648 | 0.027618 |
| 5 | 0.210783 | 1.4603 | 0.075355 |
| 6 | 0.245443 | 1.7005 | 0.047756 |
| 7 | 0.056894 | 0.3942 | 0.347599 |
| 8 | 0.081804 | 0.5668 | 0.286761 |
| 9 | 0.170133 | 1.1787 | 0.122161 |
| 10 | -0.109653 | -0.7597 | 0.774424 |
| 11 | -0.063016 | -0.4366 | 0.667817 |
| 12 | -0.343709 | -2.3813 | 0.989367 |
| 13 | -0.149445 | -1.0354 | 0.847162 |
| 14 | -0.082475 | -0.5714 | 0.714803 |
| 15 | -0.02115 | -0.1465 | 0.557941 |
| 16 | -0.07456 | -0.5166 | 0.696085 |
| 17 | 0.014732 | 0.1021 | 0.459565 |
| 18 | -0.0725 | -0.5023 | 0.69112 |
| 19 | -0.02045 | -0.1417 | 0.556039 |
| 20 | 0.012234 | 0.0848 | 0.466402 |
| 21 | -0.083474 | -0.5783 | 0.717125 |
| 22 | -0.038944 | -0.2698 | 0.60577 |
| 23 | 0.01858 | 0.1287 | 0.449057 |
| 24 | -0.018707 | -0.1296 | 0.551291 |
| 25 | 0.065265 | 0.4522 | 0.326592 |
| 26 | 0.002727 | 0.0189 | 0.492502 |
| 27 | -0.040572 | -0.2811 | 0.610076 |
| 28 | -0.141269 | -0.9787 | 0.833692 |
| 29 | -0.136475 | -0.9455 | 0.825437 |
| 30 | -0.162335 | -1.1247 | 0.866843 |
| 31 | -0.073629 | -0.5101 | 0.693847 |
| 32 | -0.095131 | -0.6591 | 0.743505 |
| 33 | -0.09281 | -0.643 | 0.73836 |
| 34 | -0.084305 | -0.5841 | 0.71905 |
| 35 | -0.103718 | -0.7186 | 0.762059 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.379818 | 2.6315 | 0.005699 |
| 1 | 0.293199 | 2.0313 | 0.023889 |
| 2 | -0.03495 | -0.2421 | 0.595147 |
| 3 | 0.159137 | 1.1025 | 0.137864 |
| 4 | 0.069198 | 0.4794 | 0.31691 |
| 5 | 0.067515 | 0.4678 | 0.321038 |
| 6 | -0.139297 | -0.9651 | 0.830328 |
| 7 | -0.023802 | -0.1649 | 0.565145 |
| 8 | 0.193904 | 1.3434 | 0.092729 |
| 9 | -0.35933 | -2.4895 | 0.991845 |
| 10 | -0.066621 | -0.4616 | 0.67676 |
| 11 | -0.298263 | -2.0664 | 0.977897 |
| 12 | 0.052721 | 0.3653 | 0.35826 |
| 13 | 0.226775 | 1.5711 | 0.061359 |
| 14 | -0.032693 | -0.2265 | 0.589114 |
| 15 | 0.220271 | 1.5261 | 0.066776 |
| 16 | 0.086561 | 0.5997 | 0.275759 |
| 17 | -0.056664 | -0.3926 | 0.651816 |
| 18 | 0.035854 | 0.2484 | 0.402442 |
| 19 | -0.070778 | -0.4904 | 0.686946 |
| 20 | 0.011457 | 0.0794 | 0.468531 |
| 21 | -0.285948 | -1.9811 | 0.973338 |
| 22 | -0.03303 | -0.2288 | 0.590018 |
| 23 | -0.150855 | -1.0452 | 0.849407 |
| 24 | 0.052926 | 0.3667 | 0.357735 |
| 25 | 0.151159 | 1.0473 | 0.150112 |
| 26 | 0.01214 | 0.0841 | 0.466661 |
| 27 | -0.038751 | -0.2685 | 0.605258 |
| 28 | -0.064915 | -0.4497 | 0.672539 |
| 29 | -0.010627 | -0.0736 | 0.529193 |
| 30 | 0.023382 | 0.162 | 0.435996 |
| 31 | -0.008916 | -0.0618 | 0.524501 |
| 32 | -0.003296 | -0.0228 | 0.509062 |
| 33 | -0.18449 | -1.2782 | 0.896335 |
| 34 | 0.032972 | 0.2284 | 0.410139 |
| 35 | -0.115605 | -0.8009 | 0.786443 |
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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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