autocorr spaarvermogen wel
| 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 | 7.6811 | 0 |
| 1 | -0.389102 | -2.9888 | 0.997961 |
| 2 | -0.00923 | -0.0709 | 0.528141 |
| 3 | 0.097965 | 0.7525 | 0.227377 |
| 4 | -0.192469 | -1.4784 | 0.927688 |
| 5 | 0.107009 | 0.822 | 0.207206 |
| 6 | 0.050509 | 0.388 | 0.349717 |
| 7 | -0.138571 | -1.0644 | 0.854253 |
| 8 | 0.083391 | 0.6405 | 0.262152 |
| 9 | -0.109455 | -0.8407 | 0.798057 |
| 10 | 0.166266 | 1.2771 | 0.103283 |
| 11 | 0.074154 | 0.5696 | 0.285561 |
| 12 | -0.33308 | -2.5584 | 0.993449 |
| 13 | 0.140549 | 1.0796 | 0.142361 |
| 14 | -0.088608 | -0.6806 | 0.75061 |
| 15 | -0.074647 | -0.5734 | 0.715714 |
| 16 | 0.120538 | 0.9259 | 0.179143 |
| 17 | -0.058944 | -0.4528 | 0.673807 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.389102 | -2.9888 | 0.997961 |
| 1 | -0.189289 | -1.454 | 0.924372 |
| 2 | 0.024494 | 0.1881 | 0.425707 |
| 3 | -0.170846 | -1.3123 | 0.902749 |
| 4 | -0.033912 | -0.2605 | 0.6023 |
| 5 | 0.063433 | 0.4872 | 0.313949 |
| 6 | -0.080561 | -0.6188 | 0.730785 |
| 7 | -0.031754 | -0.2439 | 0.595925 |
| 8 | -0.121664 | -0.9345 | 0.823078 |
| 9 | 0.13455 | 1.0335 | 0.152794 |
| 10 | 0.183396 | 1.4087 | 0.082087 |
| 11 | -0.262532 | -2.0165 | 0.975849 |
| 12 | -0.143865 | -1.1051 | 0.863188 |
| 13 | -0.113882 | -0.8747 | 0.807369 |
| 14 | -0.142409 | -1.0939 | 0.860769 |
| 15 | -0.147761 | -1.135 | 0.869511 |
| 16 | -0.050053 | -0.3845 | 0.648992 |
| 17 | 0.095467 | 0.7333 | 0.233141 |
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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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